KR20240122830A - Material handling systems and methods - Google Patents

Abstract

A material handling system for handling packages and placing said packages on pallets destined for an order counter, said system comprising a storage array, an automated package transfer system, an automated palletizer and a controller operably connected to said automated palletizer, said controller being programmed with a pallet load generator having at least one pallet with order counter friendly characteristics for a predetermined pallet load package distribution method at said order counter, said pallet load generator being configured to cause a pallet load to be formed by the automated palletizer of packages arranged on said pallet load to embody at least one pallet with order counter friendly characteristics.

Description

Material handling systems and methods

Cross-reference to related applications

This application claims the benefit of U.S. Provisional Patent Application No. 63/288,253, filed December 10, 2021, which is a non-provisional application, the entire disclosure of which is incorporated herein by reference.

Technical field

The present disclosure relates generally to material handling systems, and more specifically to handling goods and placing said goods on pallets via a material handling system.

A merchandise warehouse or distribution center generates pallets of merchandise for various customers, including but not limited to retail stores. Each of the various customers places an order for merchandise, which is fulfilled by the merchandise warehouse or distribution center by loading the ordered merchandise onto one or more pallets. Each of the various customers may have their own preferred method of depalletizing the merchandise they order from the merchandise warehouse or distribution center so that the merchandise can be easily restocked on store shelves.

The aforementioned embodiments and other features of the present disclosure are described below in connection with the accompanying drawings.

FIG. 1 is a representative schematic diagram of a warehouse or distribution center incorporating embodiments of the present disclosure.
FIG. 2 is a representative schematic diagram of distribution of palletized packages according to embodiments of the present disclosure.
FIG. 3 is a representative schematic diagram of distribution of palletized packages according to embodiments of the present disclosure.
FIG. 4 is a representative schematic diagram of distribution of palletized packages according to embodiments of the present disclosure.
FIG. 5 is a representative schematic diagram of a pallet planning order according to embodiments of the present disclosure.
FIG. 6 is a representative diagram of a palette-aisle binary matrix according to embodiments of the present disclosure.
FIG. 7 is a drawing showing a representative method according to embodiments of the present disclosure.
FIG. 8 is a representative drawing of a planned order according to embodiments of the present disclosure.
FIG. 9 is a representative diagram of a palette for a passage selection process according to embodiments of the present disclosure.
FIG. 10 is a representative drawing of the distribution of case units for pallet loads according to embodiments of the present disclosure.
FIG. 11 is a representative drawing of case unit distribution for pallet loads according to embodiments of the present disclosure.
FIGS. 12A and 12B are drawings showing representative methods according to embodiments of the present disclosure.
FIG. 13 is a diagram showing an exemplary method according to embodiments of the present disclosure.
FIG. 14 is a drawing showing a representative method according to embodiments of the present disclosure.
FIG. 15 is a drawing showing a representative method according to embodiments of the present disclosure.
FIG. 16 is a drawing showing a representative method according to embodiments of the present disclosure.
Figure 17 is a diagram showing a graph illustrating case dimension changes within a representative case group.

FIG. 1 illustrates a representative warehouse or distribution center (199) (generally referred to herein as warehouse (199)) according to embodiments of the present disclosure. Although embodiments of the present disclosure have been described with reference to the accompanying drawings, it should be understood that embodiments of the present disclosure may be embodied in many different forms. Furthermore, elements or materials of any suitable size, shape or type may be used.

Embodiments of the present disclosure are generally applicable to warehouse systems where pallet stacking (as described herein and collectively referred to as pallet stacking(s) (PALO)) is built by automated machines, such as robotized palletizers (162, 162'), according to a pallet build plan by a controller. However, embodiments of the present disclosure may also be applied to manual pallet builds where a pallet stack generator (as described herein) outputs an itemization (according to the present disclosure) of case units (CUs) to be included on a pallet, wherein a human worker builds the pallet with predetermined itemized case units (CUs) based on warehouse rules and previous work experience. Embodiments of the present disclosure may also be applied to manual warehouses where pallet build plans are generated by a computer according to the present disclosure and output in a tangible form (e.g., video monitors, graphical user interfaces, smart devices such as phones and tablets, paper instructions, etc.) to be followed by human workers in an advisory role to build the pallets described herein. Here, goods contained in pallet stacks (PALO) are conveyed to human workers in a pre-determined sequence deduced from pallet creation plans via conveyors, mobile robots or other suitable transport means.

According to the present disclosure, each pallet load (PALO) is planned by any suitable computational method, including but not limited to those described in U.S. Patent No. 8,965,559, issued Feb. 24, 2015 and U.S. Patent No. 9,969,572, issued May 15, 2018, the disclosures of which are incorporated herein by reference in their entirety. As used herein, a "planned pallet" or "planned pallet load" is a pallet load having a list of merchandise (e.g., individual items, boxes, totes, trays, etc., described herein and generally referred to as case units (CUs)) having coordinates (X, Y, Z - see FIG. 1 ) specified with respect to merchandise edges having coordinates near the origin of the pallet coordinate system (X=0, Y=0, Z=0). The orientation of the goods along the X, Y, Z axes has values for length, width, height or width, length, height for goods that may not tilt to the side, for example. Additional values may be provided for goods that may be placed on a surface on any side of the goods. These additional values include, for example, length, height, width or width, height, length or height, length, width or height, width, length. The pallet creation plan is a physically valid plan that (1) ensures that the goods do not intersect within the physical space, (2) that each of the goods is stably supported by another good or by the pallet base, (3) that no part of any good is outside the predetermined range of the pallet outer dimensions (Lp, Wp, Hp) (or the predetermined volume (Vp) of the pallet load defined by the outer dimensions (Lp, Wp, Hp)), and (4) that the total weight of the goods on the pallet does not exceed the predetermined maximum weight (Wmax) for the pallet load (PALO).

Additionally, according to the present disclosure, a "planned order" is a plurality of planned pallet lists such that all ordered case units (CU) belong to some pallets in the list and no case units (CU) belong to any pallet load. It should be noted that consecutive case units (CU) in the order list need not be assigned to the same or consecutive pallet load. For example, case unit number 1 may be assigned to pallet load number 5, and case unit number 2 may be assigned to pallet load number 3.

It should also be noted that the case units (CU) may have integer values of the "Product Group Types" that they belong to within the retail store. For example, retail stores typically assign a predetermined relationship between these Product Group Types and the physical locations (e.g., aisles, corners, sections, etc.) within the store where they are located. The Product Group Types and their corresponding physical locations within the retail store are generally referred to herein as "aisles." It should be noted that the aisles are aisles within the retail store and should not be confused with the (distribution center) storage/picking aisles of the storage array (130) of the (distribution center) material handling system (190). Here, the retail store aisles and the (distribution center) picking aisles (of the storage array (130)) are completely separate from each other. Also of note herein is that retail aisles are referenced via numeric designations ranging from 1 through n (e.g., aisle 1, aisle 2, ..., aisle n), where n is an integer value representing the highest aisle number determined in advance for any given store. Although the aisles are numbered, the locations of the aisles within the store may not be sequential. In accordance with embodiments of the present disclosure, case units (CUs) that belong to a common (e.g., same) aisle (e.g., physical location/aisle and/or product group type) are assigned to a common pallet (unless otherwise noted) for the purposes of the palletized package distribution methods described herein.

In one embodiment, aisles within a retail store that are close in number (e.g., aisles 34 and 35) may be physically close to one another in space. In such embodiments, the present disclosure can optimize the product placed on a given pallet by combining products from physically close aisles (e.g., aisles 34 and 35) on a common pallet, instead of combining products from aisles that are physically separate from one another (e.g., aisles 34 and 35).

In other embodiments, the relationship between aisle numbers and the spatial proximity of said aisles may be more complex than just adjacent aisle numbers that are physically adjacent in space (e.g., aisles 34, 35). For example, adjacent or close aisle numbers (e.g., aisle 20 and aisle 21) may not necessarily imply that the aisles are physically close to each other in space (e.g., aisle 20 may be located at one end of the retail store while aisle 21 may be located at the far end of the retail store). Here, a pairwise relationship between two aisles may be provided in connection with the allocation of case units to pallet loads as described herein. For example, according to embodiments of the present disclosure, the pairwise relationship between two aisles takes the form of coefficients A[i,k] for aisle i and aisle k. These pairwise relationships not only describe the physical proximity between two aisles, but also describe the retailer's preference to keep products from these aisles on one pallet or on separate pallets, based on retail business logic outside of distance-based load-lifting optimization. An example of such business logic might be the separation of caustic products (e.g., laundry detergent) and food products (e.g., baby food), which are preferably transported on separate pallet loads.

Embodiments of the present disclosure are also applicable to any suitable volume of products within any given aisle. For example, some aisles may have a total volume of case units that is much larger than the volume of a single pallet (e.g., see volume V2 of aisle 2 in FIG. 5 ). Here, embodiments of the present disclosure allocate the volume of the case units to the entire pallet load until the remaining volume of the case units does not fill the entire pallet load, wherein the remaining volume of the case units is allocated to the pallets according to the package distribution method described herein. As another example, the volume of the case units for other aisles may be several case units or even a single case unit, in which case such case units are allocated to the pallet load according to the package distribution method described herein.

Also referring to FIGS. 2-4, as will be described herein, the material handling system (190) of the warehouse (199) is configured to execute an optimization of an automated process for planning and building mixed product orders (299) (e.g., see FIG. 2) to be shipped to, for example, retail stores (or other suitable customers where the merchandise is shipped on pallets). The retail stores placing the orders are referred to herein as ordering stores (200) (e.g., see FIGS. 2-4). Each of the one or more pallet loads (PALOs) within the mixed product orders (299) is built by the material handling system (190) such that each pallet load (PALO) is a "store friendly pallet" or a "store friendly pallet load." By "store friendly" is meant that the pallet load (PALO) is configured for easy and efficient unloading and distribution to store shelves. For purposes of explanation only, "store friendly" means the store friendliness of a pallet load or the store friendliness of a pallet load such that the pallet load configuration (i.e., pallet load construction) as described herein includes a predetermined characteristic (or factor) of store friendliness that biases or factors the resolution of each resulting pallet load (PALO) to provide each resulting pallet load (PALO) according to the predetermined characteristics of the retailer or according to retail characteristics that are sympathetic to the predetermined characteristics of the retailer. For example, when pallet load(s) (PALO) of a fulfilled mixed product order (299) (see FIGS. 2-4) arrives at the order counter (200), the pallet load(s) (PALO) (e.g., pallet loads (PALOC) of FIG. 2, PALOA, PALOA' of FIG. 3 and PALOC, PALOC' of FIG. 4) are promptly unloaded (e.g., as in a "just in time" inventory practice) and the corresponding goods are distributed (e.g., restocked/restocked) onto counter shelves (233) with minimal disruption to counter operations. To facilitate rapid unloading and distribution of merchandise onto the store shelves (233), the material handling system (190) is configured to structure the pallet stack(s) (PALO) so that the merchandise CUs (herein, packages, products, case units, mixed cases, cases, case units of pallet stack PALO, mixed cases, cases, shipping cases and shipping units) on the pallet stack(s) are grouped in a manner similar to the manner in which the merchandise CUs are distributed onto the store shelves (233).

Each warehouse customer (e.g., order counter (200)) of a warehouse (199) may have its own preferences with respect to the handling of pallet loads within the order counter (200). Embodiments of the present disclosure provide for the construction of store-friendly pallets that correspond to the various ways in which pallet loads are handled and products are distributed by warehouse customers.

Referring to FIG. 2, one exemplary method of handling pallet loads (PALO) may be referred to as a “cluster aisle pallet load package distribution method” and includes dismounting/downstacking pallet load(s) (PALOC) within the loading dock area (222) (or other suitable area) of the order counter and placing merchandise CUs belonging to different sections of the order counter (200) onto two or more separate auxiliary pallets (PAL21-PAL23) (three auxiliary pallets are shown in FIG. 2 for illustrative purposes only). These auxiliary pallets (PAL21-PAL23) contain merchandise CUs assigned to predetermined shopping aisles and are moved into the corresponding predetermined shopping aisles for unloading (see FIG. 2). If there are auxiliary pallets (PAL21-PAL23) in the corresponding shopping aisle, product CUs from the auxiliary pallets (PAL21-PAL23) are distributed onto the assigned shelf (233).

Referring to FIG. 3, another example of handling pallet loads (PALO) may be referred to as an "adjacent aisle pallet load package distribution method" and involves moving entire pallet loads (PALOA, PALOA') into the shopping aisles (e.g., without downstacking the pallets). When the pallet loads (PALOA, PALOA') are within the shopping aisles, the merchandise CUs are substantially distributed directly from the pallet load(s) (PALOA, PALOA') to their assigned shelves (233) (see FIG. 3). Here, merchandise is placed on the pallet load(s) (PALOA, PALOA') so as to minimize the travel distance of each pallet load(s) (PALOA, PALOA') within the store and substantially prevent the pallets (PALOA, PALOA') from returning to aisles that the corresponding pallets have previously visited (e.g., the pallets traverse the aisles only once along a predetermined path (301, 302)). The product CU can be placed on the pallet load (PALO, PALOA') according to the movement path (300, 302) of the corresponding pallet load (PALOA, PALOA') through the shopping aisles.

Referring to FIG. 4, another example of handling pallets (PALO) may be referred to as a "mixed mode clustering and adjacent aisle pallet stack package distribution method" and includes a combination of the above handling methods. Referring to FIG. 4, pallet loads (PALOC, PALOC') arrive at an order counter (200) from a warehouse/distribution center (199) by truck (or other suitable transport means). The pallet loads (PALOC, PALOC') are moved (without downstacking the pallets) into a shopping area near a shelf to which a merchandise CU on the pallet loads (PALOC, PALOC') is assigned. When pallet loads (PALOC, PALOC') are generally located near the assigned shelf, the pallet loads (PALOC, PALOC') are downstacked into corresponding auxiliary pallets (PALO21, PALO22, PALO23, PALO21', PALO22') assigned to corresponding shopping aisles. Here, the pallet loads (PALOC, PALOC') are constructed such that each pallet load (PALOC, PALOC') includes merchandise belonging to/assigned to store aisles that are close to each other (e.g., pallet load (PALOC) includes merchandise located in aisle 1, aisle 2 (adjacent to aisle 1), and aisle 4 which is just one aisle away from aisle 2; similarly, pallet load (PALOC') includes merchandise belonging to/assigned to adjacent aisles 12 and 13). A product CU may also be arranged within a corresponding pallet load (PALOC, PALOC') such that the pallet structure corresponds to the manner in which the products are downstacked on the corresponding auxiliary pallets (e.g., sequential downstacking such that the product assigned to the auxiliary pallet (PALO21) is on the top of the pallet structure of the pallet load (PALOC), the product assigned to the auxiliary pallet (PALO22) is in the center of the pallet structure of the pallet load (PALOC), and the product assigned to the auxiliary pallet (PALO23) is on the bottom of the pallet structure of the pallet load (PALOC). In such an embodiment, the aisles to which the product CU is assigned may not be arranged along a corresponding specific path (e.g., see paths (301, 302) of FIG. 3) for unloading the product CU of the corresponding pallet load (PALO, PALO') onto the store shelf.

The examples of pallet handling/downstacking methods in the ordering point (200) described above are merely examples. It should be noted again here that the pallet loads (PALOC, PALOC', PALOA, PALOA') for each of the pallet handling/downstacking methods are generally referred to herein as pallet loads (PALO). It should also be noted here that the merchandise on the pallet load(s) (PALO) may be arranged in any suitable manner by the material handling system (190) so as to be arranged according to any suitable at least one order pallet for the ordering point friendly characteristics (166, 166') for the pallet load package distribution methods described herein. It should be noted here that the ordering point friendly pallet separation (as described herein) is separated from the arrangement of the storage array (130) and the throughput of the material handling system (190) of the cases (CU) to the palletizer (162). Here, the output of cases (CU) from the storage array (130) by the material handling system (190) is selected to be based on or dependent on the store friendly pallet load sorting. In one or more embodiments, the throughput of cases (CU) output by the material handling system (190) can be effected in a manner similar to that described in U.S. patent application Ser. No. 17/091,265, filed Nov. 6, 2020, entitled “Pallet Building System with Flexible Sequencing,” the entire disclosure of which is incorporated herein by reference. According to embodiments of the present disclosure, the arrangement of cases (CU) within the storage array (130) can be freely optimized for optimal throughput separately from the sorting and building of the store friendly pallet loads (PALOs). An example of throughput optimization is found in U.S. Pat. No. 9,733,638, issued Aug. 15, 2017, entitled “Automated Storage and Retrieval System and Control System Thereof,” which is incorporated herein by reference in its entirety.

Referring to FIG. 1 , a materials handling system (190) may be positioned within a retail distribution center or warehouse (199) to fulfill orders received from, for example, retail stores (e.g., order kiosks - see FIGS. 2-4 ) to dispense merchandise shipped in cases, packages, and/or parcels. The terms case, package and parcel are used interchangeably herein and may refer to any container that can be used for shipment as noted above and may be filled by a manufacturer with one or more units of product. Case or cases, as used herein, means case, package or parcel units that are not stored (e.g., not contained) in trays, on totes, or the like. It should be noted that case units (CU) may include cases of articles/units (e.g., cases of soup cans, cereal boxes, etc.) or individual articles/units suitable for removal from or placement on a pallet. According to the present disclosure, case units (e.g., cartons, barrels, crates, jugs, shrink-wrap trays or groups or any other suitable device for holding merchandise) may be of various sizes and may be configured to hold merchandise when shipped and to be palletized for shipment. Case units (CU) may include totes, boxes and/or containers holding one or more merchandise that has been unpackaged or disassembled from its original packaging (generally referred to as breakpack goods) and may be placed within totes, boxes and/or containers (collectively referred to as totes) holding one or more other individual merchandise of mixed or common types at an order filling station. It is to be noted here that when incoming bundles or pallet loads (PALNs) (e.g., from manufacturers or suppliers of case units) arrive at the MHS (190) for replenishment of merchandise stored within the storage array (130) of the MHS (190), the contents of each pallet load (PALN) may be uniform (e.g., each pallet contains a predetermined number of identical items - one pallet contains soup and another pallet contains cereal). As may be realized, the cases of such pallet loads (PALNs) may be substantially similar or, in other words, homogeneous cases (e.g., similar dimensions) and may have identical SKUs (if not, the pallets may be "rainbow" pallets having layers of homogeneous cases, as noted above).

As pallet loads (PALOs) leave the material handling system (190) to fill store replenishment orders, the pallet loads (PALOs) may include any suitable number and combination of different case units (e.g., each pallet may hold a different type of case unit - a pallet may hold a combination of canned soups, cereals, beverage packs, cosmetics, and household cleaners). The cases combined on a single pallet may have different dimensions and/or SKUs.

A material handling system (190) typically includes a storage array (130) and an automated package transport system (195). The storage array (130) includes a storage space (130S) for holding case units (CU) therein. The automated transport system (195) is communicatively connected to the storage array (130) to store case units (CU) within the storage space (130S) of the storage array (130) and to retrieve case units (CU) from the storage space (130S) of the storage array (130).

An automated palletizer (162, 162') includes an automated package pick device (162D) (e.g., a robotic arm, a gantry picker, etc.) capable of moving case units (CU) from a package deposit section (such as an out-feed transfer station; 160) onto a pallet (referred to herein as a pallet base) to form a pallet load (PALO) from the case units (CU), wherein the pallet load (PALO) includes more than one composite layer (L1-Ln) of case units (CU). As described herein, one or more composite layers (L1-Ln) of case units (CU) are formed of case units (CU) arranged within the pallet load (PALO) to embody at least one pallet according to order store friendly characteristics (166, 166') for a pre-determined pallet load package distribution method at the order store (see FIGS. 2 to 4). The automated palletizer (162, 162') is communicatively connected to the automated package transfer system (195). The automated package transfer system (195) provides individual case units (CU) from the storage array (130) to the automated palletizer (162) to form a pallet load (PALO), wherein the pallet load (PALO) comprises one or more composite layers (L1-Ln) of case units (CU). Individual case units (CU) from a storage array (130) upon which the above pallet stack (PALO) is constructed have case dimensions (e.g., any one or more of case length, case width and case height), wherein the case dimension(s) have a substantially Gaussian distribution or substantially probabilistic probability represented by a normal probability curve as illustrated in FIG. 17. FIG. 17 illustrates a graph depicting the variation in case dimensions (e.g., length, height and width) within a population of representative cases (CU) that may be found in a material handling system (190) and used to generate mixed case pallet stacks (PALO) based on customer supply orders (as described herein). As may be realized, the orders may cause the mixed case pallet stacks (PALO) to have dimensions from different portions of the dimensional spectrum illustrated in FIG. 17.

A controller (164, 164') is operatively connected to the automated palletizer (162). The controller (164, 164') is programmed with non-transitory computer program code defining a pallet load generator (165, 165') having at least one pallet according to order point friendly characteristics (166, 166') (as described herein) for distributing case units (CU) of a pallet load (PALO) in a predetermined manner at the order point (200). As described herein, the pallet load generator (165, 165') is configured to cause the automated palletizer (162) to form case units (CU) disposed within the pallet load (PALO) so as to embody at least one pallet according to the order point friendly characteristics (166, 166').

More specifically now, and still with reference to FIG. 1 , the material handling system (190) may be configured for installation in existing warehouse structures, for example, or may be adapted for new warehouse structures. As previously noted, the material handling system (190) illustrated in FIG. 1 is representative and may include, for example, corresponding input and output transfer stations (170 , 160 ), lift module(s) (150A, 150B), a storage array (130 ) (e.g., including suitable structures such as racks, vehicle boarding surfaces, storage shelves, etc.), and input and output conveyors terminating on a plurality of autonomous transport vehicles (110) (referred to herein as "bots") (e.g., for transferring case units from and to corresponding depalletizers (162') and palletizers (162 ).

It should be noted that the material handling system (190) is formed by at least the storage array (130) and the boats (110). In some embodiments, the lift modules (150A, 150B) also form part of the material handling system (190), however, in other embodiments, the lift modules (150A, 150B) may form vertical sequencers in addition to the material handling system, as described in U.S. patent application Ser. No. 17/091,265, filed Nov. 6, 2020, entitled “Pallet Building System with Flexible Sequencing,” the entire disclosure of which is incorporated herein by reference. In alternative embodiments, the material handling system (190) may also include a robot or robotic transfer station (140) that may provide an interface between the boats (110) and the lift module(s) (150A, 150B).

The storage array (130) comprises any suitable structure forming multiple (stacked) storage levels (130L1-130Ln) of storage rack modules (generally referred to as storage levels (130L) or storage level (130L), where n is an integer representing the upper number of the storage levels present in the material handling system (190), see FIG. 1), each level (130L) comprising corresponding picking aisles (130A), storage spaces (130S) and transfer decks (130B) for transferring case units between any one of the storage spaces (130S) of the storage structure and the shelves of the lift module(s) (150A, 150B). The above storage spaces (130S) are arranged along one or more sides of each picking aisle (130A) (or parallel to one or more sides) so that boats (110) moving along the picking aisle (130A) can access the storage spaces (130S) from both sides of the picking aisle (130A).

The picking aisles (130A) are configured in one embodiment to provide guided movement of the boats (110) (e.g., along a vehicle boarding surface (VRSR) including boat guidance features such as rails), while the picking aisles are configured in other embodiments to provide unrestricted movement of the boats (110) (e.g., along an open and indeterminate vehicle boarding surface (VRSU) for boat (110) guidance/movement). The transfer deck (130B) has an open and indeterminate boat support moving surface (VRS) along which the boats (110) move under guidance and control provided by the boat steering (e.g., such steering is effected by one or more of differential drive wheel steering, steerable wheels, etc.). In one or more embodiments, the transfer decks (130B) have multiple lanes that the boats (110) can freely switch to access the picking aisles (130A) and/or the lift modules (150A, 150B). The picking aisles (130A) and transfer decks (130B) also allow the boats (110) to place case units (CU) into picking stock and retrieve ordered case units (CU). In alternative embodiments, each storage level (130L) may also include corresponding boat transfer stations (140) that provide a case unit transfer interface between the boats (110) and the lift module(s) (150A, 150B).

The above boats (110) are configured to place case units (CU), such as the retail items described above, into a picking stock within one or more levels (130L) of the storage array (130), and then selectively retrieve ordered case units (CU) for distribution to, for example, an ordering kiosk (200) (see, e.g., FIGS. 2-4 ) or other suitable location.

The above inlet transfer stations (170) and outlet transfer stations (160) are operable with their corresponding lift module(s) (150A, 150B) to bidirectionally transfer case units (CU) to and from one or more levels (130L) of the storage structure (130). It should be noted that while the lift modules (150A, 150B) may be described as being dedicated inbound lift modules (150A) and outbound lift modules (150B), in alternative embodiments each of the lift modules (150A, 150B) may be used for both inbound and outbound transfers of case units from the material handling system (190). Likewise, while the palletizers (162, 162') may be described as being dedicated (inbound) palletizers (162') and (outbound) palletizers (162), in alternative embodiments, each of the palletizers (162, 162') may be used for both inbound and outbound transfer of case units from the material handling system (190).

As may be realized, the material handling system (190) may include a plurality of inlet and outlet lift modules (150A, 150B) accessible, for example, by boats (110) of the material handling system (190), such that one or more case unit(s) that are not contained (e.g., case unit(s) not held within trays) or one or more case unit(s) contained (within trays or totes) may be transferred from the lift modules (150A, 150B) to a respective storage space (130S) on a corresponding level (130L), and from each storage space (130S) to one of the lift modules (150A, 150B) on a corresponding level (130L). The above boats (110) can be configured to transfer the case units between the storage spaces (130S) (e.g., located within the picking aisles (130A) or other suitable storage spaces/case unit buffers arranged along the transfer deck (130B)) and the lift modules (150A, 150B). In general, the lift modules (150A, 150B) include at least one movable payload support capable of moving the case units (CU) between the inlet and outlet transfer stations (160, 170) and a corresponding level (130L) of the storage space (130S) where the case units (CU) are stored and retrieved. The lift module (s) may have any suitable configuration, such as, for example, a reciprocating lift, or any other suitable configuration. The lift module (s) (150A, 150B) include any suitable controller (such as the controller (120) or other suitable controller coupled to the controller (120), the warehouse management system (2500) and/or the palletizer controller (164, 164')), and is described in U.S. Patent Application Publication No. 2019-06-18 entitled "Vertical Sequencer for Product Order Fulfillment". A sequencer or classifier may be formed in a manner similar to that described in U.S. Pat. No. 16/444,592, the entire disclosure of which is incorporated herein by reference.

The materials handling system (190) may include a control system including one or more control servers (120) communicatively coupled to the inlet and discharge conveyors and transfer stations (170, 160), the lift modules (150A, 150B), and the boats (110) via, for example, a suitable communications and control network (180). The communications and control network (180) may have any suitable architecture that may incorporate various programmable logic controllers (PLCs), such as for providing commands to the operation of the inlet and discharge conveyors and transfer stations (170, 160), the lift modules (150A, 150B), and other suitable system automation. The control server (120) may include advanced programming that affects a case management system (CMS) for managing the flow of cases through the materials handling system (190).

The network (180) may further include suitable communications to perform a bidirectional interface with the boats (110). For example, the boats (110) may include an on-board processor/controller (1220). The network (180) may include a suitable bidirectional communications suite that enables the boat controller (1220) to request or receive commands from the control server (120) to perform desired transports of case units (CU) (e.g., placing into or retrieving from storage locations) and to transmit desired boat (110) information and data, including ephemeris, status, and other desired data, of the boat (110) to the control server (120).

As can be seen in FIG. 1, the control server (120) may be further coupled to a warehouse management system (2500) for providing inventory management and customer order fulfillment information to the CMS (120) level program, for example. A suitable example of a material handling system arranged to hold and store case units is described in U.S. Patent No. 9,096,375, issued Aug. 4, 2015, the entire disclosure of which is incorporated herein by reference.

Referring to FIGS. 1 to 5 , embodiments of the present disclosure will now be described in more detail, wherein the pallet stack (PALO) is constructed according to at least one pallet for an order point friendly characteristic. As mentioned above, the at least one pallet for the order point preferred characteristic (166, 166') is at least one (e.g., predetermined customer friendly) of a cluster aisle pallet load package distribution method (e.g., see FIG. 2 ), an adjacent aisle pallet load package distribution method (e.g., see FIG. 3 ), a mixed mode cluster and adjacent aisle pallet load package method (e.g., see FIG. 4 ). At least one pallet for the order point friendly feature (166, 166') may be stored in any suitable memory, such as the memory of the control server (120) and/or the palletizer (162, 162') described herein, and may be employed by the control server (120) and/or the palletizer (162, 162') to generate pallet loads (PALOs) described herein. The term aisle as used hereinafter refers to an order point aisle in which a pallet load (PALO) is defined, unless otherwise specified.

Referring to FIGS. 1 and 5 , a representative graph (see FIG. 5 ) for a sample order for pallet planning is illustrated and includes case units from one or more aisles of an order kiosk (200) (FIGS. 2 to 4 ). In the representative sample order illustrated in FIG. 5 , the aisles are numbered 1 through 12. The total volumes V1 through V12 of case units (CU) ordered for each corresponding aisle 1 through 12 are represented by the height of the corresponding bar in the graph (each bar corresponding to a corresponding aisle 1 through 12). The volumes V1 through V12 are depicted as fractional units relative to an expected total volume Vp of case units (CU) on an overall pallet load (e.g., an overall pallet load having maximum pallet load dimensions of length Lp , width Wp , and height Hp ). The volume Vp is the product of the expected volumetric efficiency E of the packed products on the pallet stack and the maximum dimensions Lp (length), Wp (width), Hp (height) (e.g., of the space allocated for case units (CU) on the pallet stack), where

(Formula 1)

Has the same relationship as

Typically, the dimensions (e.g., length, width, height) of the goods/case units (CU) are known such that the case units (CU) have a general rectangular parallelepiped shape. Here, the known dimensions of the case units provide for the determination of the total volume Vp of the case units (CU) (e.g., the combined volume of the case units (CU) assigned to any given pallet load). As an example, and depending on the calculation method for planning the individual pallet loads, the average total product volume on a pallet is statistically about 0.8 if the standard deviation of the outer boundary volume of a pallet load having the dimensions Lp (length) x Wp (width) x Hp (height) is 0.03 (e.g., about 80% of the pallet volume is occupied by goods, the remainder is empty space between the goods). The expected efficiency E depends on the packing algorithms of the computational method (such as the one described herein) and should generally exceed a value of about 0.8 for state-of-the-art packing algorithms (such as the one described herein) and for mixed products containing boxes of various dimensions.

Referring generally to FIG. 5 , it can be seen that some of the aisles 1 through 12 (e.g., see aisle 2 ) may have a total volume (such as the volume V2 of aisle 2 ) that exceeds the expected (maximum) volume Vp of a single pallet load (PALO). Other aisles 1 through 12 may have corresponding volumes that are less than or equal to the expected total volume Vp (e.g., the volume V9 of aisle 9 ). As described herein, in accordance with embodiments of the present disclosure, the pallet load generator (165 , 165 ') (e.g., of the control server (120) and/or the palletizer (162 , 162 ')) is configured to resolve the pallet load (PALO) according to at least one pallet for the order point friendly characteristic (166 , 166 ') such that the pallet load (PALO) has one or more of the following:

Maximized for at least one of the maximum pallet load volume Vp and the maximum pallet load weight Wmax,

Carry the maximum number of packages from the minimum number of store aisles;

Each store order is generated to have a minimum number of pallet loads,

For each pallet load scheduled to an order counter (200), case units (CU) forming the pallet load are generated to represent the minimum number of order counter aisles, and

For each pallet load scheduled to an order counter (200), a resolved pallet load is generated that represents the minimum number of order counter aisles.

With reference to FIGS. 1, 2, 5, 6, 7, 8, and 12, a pallet to order point friendly characteristic (166, 166') for a clustered aisle pallet load package distribution method will be described in more detail. The clustered aisle pallet load package distribution method minimizes both (1) the number of pallets generated from a given set of products and (2) the average pallet per aisle ratio (RPA). The pallet per aisle ratio (RPA) is determined as the total number of instances of products from each aisle on each pallet divided by the total number of aisles. The pallet per aisle ratio (RPA) can be understood as the number of times a pallet load (PALO) is present in any aisle or the number of aisles in which a pallet load (PALO) is present for unloading. This number is sought to be minimized (e.g., sought to be close to 1).

The pallet-aisle ratio (RPA) can be expressed as a pallet-aisle binary matrix (PA) as illustrated in FIG. 6. Here, the pallet-aisle binary matrix (PA) has the number of rows equal to the number of aisles (eight aisles are illustrated for the purpose of illustration) and the number of columns equal to the number of pallets planned for a given order (four pallets are illustrated for the purpose of illustration). If the product of aisle (i) is on pallet (j), the element of the pallet-aisle binary matrix (PA[i,j]) at row (i) and column (j) is equal to 1, otherwise the element of the pallet-aisle binary matrix (PA[i,j]) at row (i) and column (j) is equal to 0. The pallet-aisle ratio (RPA) is determined by dividing the sum of all elements of the pallet-aisle binary matrix (PA) by the number of aisles that contain the products included in the order. It is important to note here that if all aisles are occupied by only one pallet, the RPA is equal to 1. The RPA becomes higher as more products from some aisles are spread across multiple pallets. If products from all aisles are on all pallets, the RPA is equal to the number of pallets. In the example illustrated in Figure 6, the RPA is equal to 11/8 or 1.375. Here the RPA is greater than 1 because products from aisle 1 are on pallets 1 and 3, products from aisle 6 are on pallets 2 and 4, and products from aisle 8 are on pallets 1 and 4.

In a cluster aisle pallet loading package distribution method, all single-aisle pallets are planned for aisles having a volume in case units (CU) exceeding the expected pallet volume Vp or maximum pallet weight Wmax, as will be described more specifically herein. The remaining pallets to fill the store orders are planned from combinations of aisles employing an iterative double-loop decision, as illustrated in FIG. 12a, where the pallets are planned for each aisle combination iteration (IAi) (e.g., nested within a relatively wide pallet building iteration (Pj)) such that the volume (Vc)(IAi) is maximized with respect to the expected pallet volume (Vp) (e.g., to minimize the number of pallets in the order) and the pallet per aisle ratio (RPA) is minimized (e.g., to approach 1). Here, the iterative double-loop decision is repeated through the combinations of aisles until a planned pallet (as will be described in more detail below) is successfully planned and the pallets are repeated until the entire aisle order is consumed (e.g., filled) and there are no more unplanned (i.e., unassigned to a pallet load) case units (CU) of the aisle order. Here, the order aisle affinity characteristic (166, 166') is informed by the iterative double-loop decision in which at least one loop associates order aisles with each other. At least another loop of the iterative double-loop decision determines available combinations of order aisles that disassemble the arrangement of case units or packages (CU) within a given pallet load (PALO). The iterative double-loop decision is illustrated, for example, in FIGS. 7 and 12b and will be described hereinafter for pallet load construction according to the order aisle affinity characteristic for a cluster aisle pallet load package distribution method.

The warehouse management server (2500) or the control system (120) (or any other suitable controller of the warehouse (199)) receives a store order (FIG. 12b, block (1200)). When the warehouse management server (2500) receives the store order, the store order is transmitted to the control server (120) via the network (180) or in any other suitable manner. The control server (120) instructs the automated package transfer system (195) to retrieve the ordered goods from the storage array (130) for transport to the palletizer (162). For example, boats (110) on one or more predetermined storage levels (130L1-13Ln) are commanded by a control server (120) to retrieve ordered case units (CU) from predetermined storage spaces (130S) of corresponding storage levels (130L1-130Ln). The boats transport the retrieved case units (CU) from the storage spaces (130S) to the lift(s) (150B) so that they are output to the palletizer via the discharge transfer station (160) in a predetermined order. Here, the predetermined order of case unit (CU) output is at least partially determined by the ordering kiosk friendly characteristics (166, 166').

One or more of the control server (120) and the palletizer (162) are configured to determine a pallet for an ordering point affinity characteristic (166, 166') based on, for example, an ordering point (200) placing an order (FIG. 12b, block (1210)). For example, one or more of the palletizer controllers (164, 164') of the control server (120) and the palletizer (162) are configured with a pallet load generator (165, 165'). For example, in one embodiment, each corresponding order kiosk (200) may notify the pallet load generator of its corresponding pallet for the order kiosk affinity feature (166, 166') prior to placing an order (such as when the order kiosk opens an account with the warehouse (199), or at any other suitable time, and when the pallet for the order kiosk affinity feature (166, 166') is communicated with or entered into the warehouse management system). Here, the pallet load generator (166, 166') may include any suitable table associating each order kiosk (200) with its corresponding pallet for the order kiosk affinity feature (166, 166'). In other embodiments, the pallet for the order kiosk friendly feature (166, 166') may be delivered to the pallet load generator (165, 165') concurrently with placing an order (such as entering an order submission), where the pallet load generator determines the pallet for the order kiosk friendly feature (166, 166') substantially directly from the order, regardless of the identity of the order kiosk (200). As noted above, in this example the pallet for the order kiosk friendly feature (166, 166') is for a cluster aisle pallet load package distribution method.

The pallet load generator (165, 165') determines any aisles having a total volume of case units (Vcomb) greater than the expected volume (Vp) of the pallet load (PALO) (block (700A) of FIG. 7) (in the example shown in FIG. 5, aisle 2 has a volume (V2) greater than the expected volume (Vp). Alternatively, the pallet load generator (165, 165') determines any aisles having a total weight of case units (Wcomb) greater than the expected weight (Wmax) (e.g., maximum weight) of the pallet load (PALO). Any aisles having a total volume of case units (Vcomb) greater than the expected volume (Vp) or a total weight of case units (Wcomb) greater than the expected weight (Wmax) (collectively referred to herein as "aisles-in-excess"). Based on the presence, the pallet load generator (165, 165') plans pallet loads (PALO) that are fully formed with case units ordered for the excess aisles and belonging to the excess aisles (FIG. 7, block (710)). In some embodiments, there are some case units (CU) remaining from the excess aisles that are included in subsequent pallet loads (FIG. 7, block (720)). For example, the pallet load generator (165, 165') forms pallet load 1 (see FIG. 8) with a portion (V2A) of the case unit volume (V2) from FIG. 5, but the remaining portion (V2B) of the case unit volume (V2) from FIG. 5 is included in pallet load 5, as will be described below.

Subsequent pallet loads (or pallet loads without excess aisles) are planned from a single aisle or from a combination of more than one aisle. As described herein, the aisle combinations are computationally generated by the pallet load generator (165, 165') to minimize the pallet-per-aisle ratio and maximize the case unit volume of each pallet load (PALO). Wherein each of the available aisle combinations of the order aisles is determined based on maximizing the pallet load or, in other embodiments as described herein, maximizing the combination of pallet loads and contiguous or adjacent aisles within the available combination, wherein maximizing the pallet load has a higher weight than contiguous or adjacent aisles.

Each of the subsequent pallet loads has a total volume of case units (Vcomb) that is less than the expected product volume (Vp) of the pallet load (PALO), and a total weight of case units (Wcomb) that is less than the expected weight (Wmax) of the pallet load (PALO). Each of the aisle combinations can have a different number of aisles, from one aisle to the total number of aisles remaining in the order. A list of allowed aisle combinations (ALC) (see FIG. 1) can be determined by employing a binary representation of an integer iterator (FIG. 7, block (730)), where the integer iterator has a value k ranging from 1 to 2 ^Na -1, where Na is the number of aisles remaining in the order. Each increment of this integer iterator corresponds to a potential aisle combination as follows: If the mth bit from the least significant bit of the binary representation of the integer iterator is 1, then aisle m from the remaining aisle list is present in the combination, and if the least significant bit is 0, then aisle m is excluded from the combination.

As an example of the use of integer iterators, consider a kiosk order with 5 aisles (or more or less) and an integer iterator of 12, i.e. the 12th iteration (note that the 11th of a possible 31 iterations occurred before the 12th iteration (in this example the range of the integer iterator is from 1 to 31, as determined by k = 2 ^Na -1 = 2 ⁵ -1 = 31 iterators/iterations) and subsequent iterations can occur after the 12th iteration as long as the aisles remain in the order). The binary representation of the number 12 (i.e. the integer iterator) is 01100. The numbers of aisles, arranged in order from the top to the bottom, can be arranged in a grid for the binary representation of the integer iterator (so that the numbers of aisles align with the corresponding numbers in the binary representation of the integer iterator), as shown in Table 1 below:

Number of passages 5 4 3 2 1 Bit values of integer iterator 0 1 1 0 0

As mentioned above, if the bit of the integer iterator corresponding to a passage is 1, then the case units (CU) from that passage are present in the passage combination. In the example provided above, the bits of the integer iterator corresponding to passages 4 and 3 are 1, which means that the case units (CU) from passages 4 and 3 are included in the 12th iterative combination of passages, while passages 5, 2 and 1 are excluded from the 12th iterative combination of passages.

For each value k of the integer iterator, the total volume (Vcomb) and weight (Wcomb) of the case units (CU) within the aisle (e.g., the corresponding aisle combination for any given value k of the integer iterator) are determined and compared by the pallet load generator (165, 165') using the expected pallet volume (Vp) and the maximum pallet weight (Wmax). If either of the values of Vcomb and Wcomb exceeds the values of Vp and Wmax, respectively, then the aisle combinations having at least one of the values of Vcomb and Wcomb that exceeds the values of Vp and Wmax are discarded. If both of the values of Vcomb and Wcomb are less than the values of Vp and Wmax, respectively, then the aisle combinations having both values of Vcomb and Wcomb that are less than the values of Vp and Wmax are added to the list of allowed aisle combinations (ALC). Referring to the above example, the combined volumes V3 and V4 of aisles 3 and 4 must be less than or equal to the expected pallet volume (Vp), respectively, and the combined weights W3 and W4 of aisles 3 and 4 must be less than or equal to the maximum pallet volume (Vp), respectively, to be included in the list of allowed aisle combinations (ALC).

The list of allowed aisle combinations (ALC) may be sorted in any suitable manner, such as in descending order of the total (case unit) volume (Vcomb) of each of the aisle combinations. Sorting the list of allowed aisle combinations in descending order of the total case volume (Vcomb) may provide for building the fewest number of pallets for any given store order. The list of allowed aisle combinations (ALC) serves as a candidate list of combinations of products selected for planning a pallet load out (PALO) from the output pallet list for any given store order.

A representative sorted list of allowed channel combinations (ALCs) of 10 channels can be presented as shown in Table 2 below:

passage combination 1 Aisles 2, 3, 8 Vcomb/Vp = .99 passage combination 2 Aisles 1, 4, 6, 9 Vcomb/Vp = .98 passage combination 3 passages 3, 7 Vcomb/Vp = .98 passage combination 4 Aisles 4, 5, 10 Vcomb/Vp = .96

Here, the rightmost column represents the total volume ratio of the case units in the corresponding aisles within the aisle combination (i.e., combination volume (Vcomb)) to the expected pallet volume (Vp).

It should be noted here that in embodiments where the number of aisles involved in a store order is large, each aisle may be subdivided into any suitable number of aisle segments, where the size of the aisle segments may depend on the computational resources of the pallet stack generator (165, 165'). The size of the aisle segments may also affect the minimum number of pallets generated/output by the warehouse (199) for any given store order. The aisle segments are grouped with other aisle segments such that each aisle segment is treated as one aisle and a list of aisle combinations (ALCs) are determined for each of the store segments in the manner described above.

As mentioned above, the pallets for the order picker friendly characteristics for the cluster aisle pallet load package distribution method are informed by an iterative double loop (DRL) determination where at least one loop determines available combinations of order picker aisles that disassemble the arrangement of packages within the pallet load and at least another loop associates the order picker aisles with each other. In the iterative double loop (DRL), the pallet loads are planned by employing a list of aisle combinations (ALC).

In one loop of the repetitive double loop (DRL), the pallet load generator (165, 165') determines available aisle combinations for disassembling the package array within the pallet load (Fig. 12b, block (1230)). An input from the list of aisle combinations (ALC) with the highest Vcomb/Vp ratio (which is aisle combination 1 in the example above) is selected (Fig. 7, block (735)) and the pallet load (PALO) is planned with case units (CU) corresponding to the aisles within the selected aisle combination (Fig. 7, block (740)), thereby optimizing for the minimum number of pallets. If the pallet plan for the selected aisle combination does not fit all the case units from the aisles of the selected aisle combination in the pallet load (PALO) (which means that some of the case units of the corresponding aisles remain unpacked for inclusion in other pallets, thus verifying or validating the optimization of the pallet rate per aisle (RPA) - FIG. 7 , block (745) -), the pallet plan is discarded (FIG. 7 , block (750)). The next entry from the list of aisle combinations (ALC) with the next highest Vcomb/Vp ratio (e.g., the next aisle combination 2 in the example above) is selected (FIG. 7 , block (735)), thereby performing the optimization again for the minimum number of pallets. The pallet load (PALO) is planned with case units (CU) corresponding to the aisles in the next aisle combination (FIG. 7 , block (740)), where blocks (740, 745, 750, 735) are A pallet plan for an input selected from a list of aisle combinations (ALC) is iterated (for subsequent aisle combinations, e.g., aisle combination 2, aisle combination 3, aisle combination 4, etc.) until the pallet plan successfully packs all case units for corresponding aisles in a pallet stack (e.g., pallet stack (PALO)) and the optimization of the pallet per aisle rate (RPA) is reconfirmed or verified. Here, the aisle combinations are analyzed sequentially by the pallet stack generator (165, 165') through an iterative double loop (DRL) determination of the pallet plan until a planning solution is found that includes all case units ordered for the aisles in said aisle combination.

As an example of the sequential analysis of the aisle combinations, using the aisle combinations 1 through 4, the pallet load generator (165, 165') first analyzes aisle combination 1 (aisles 2, 3, 8) to determine whether all case units (CU) ordered for aisles 2, 3, and 8 are suitable for a single pallet load having a maximum volume (Vp) and maximum weight (Wmax). For illustrative purposes, assume that not all case units ordered for aisles 2, 3, and 8 are suitable for a single pallet load, and therefore the next aisle combination in the aisle combination sequence (e.g., aisle combination 2) is analyzed. Here, the pallet load generator (165, 165') analyzes the aisle combination 2 (aisles 1, 4, 6, and 9) to determine whether all case units (CU) ordered for aisles 1, 4, 6, and 9 fit into a single pallet load having a maximum volume (Vp) and a maximum weight (Wmax). For illustrative purposes, it is assumed that all case units ordered for aisles 1, 4, 6, and 9 fit into a single pallet load, and thus the decision loop that sequentially analyzes the aisle combinations stops and the remaining aisle combinations (e.g., aisle combinations 3 and 4) are not analyzed. As will be described below, any subsequent pallet load is generated with an updated set of aisle combinations (separate from the previous set of aisle combinations and excluding the aisles from which all case units ordered were assigned to pallet loads).

A successful pallet plan (aisle combination 2 in the example above) forms a planned pallet load (PALO) and is added to the output list (FIG. 7, block (755)) that is executed by the automated package transfer system (195), thereby causing the automated package transfer system (195) to pick and sort case units (CU) from the planned pallet load (PALO) (FIG. 12b, block (1220)) to build the planned pallet load at the palletizer (162) (FIG. 12b, block (1250)). In some embodiments, case unit picking and pallet building for a given store order may occur substantially simultaneously with subsequent pallet load planning within that store order, while in other embodiments, case unit picking and pallet building may occur after all pallets have been planned for that store order.

In another loop of the repetitive double loop (DRL) in which the planned pallet load (PALO) is successfully planned, the pallet load generator (165, 165') determines if there are any case units (CU) from any aisle in the store order that are not included in the (successfully) planned pallet load (PALO) (FIG. 7, block (760)). If there are no more case units (CU), the pallet planning is stopped (FIG. 7, block (765)) and the case units (CU) of the planned pallet loads (PALO) for the store order are retrieved from the storage and sorted by the automated package transfer system (195) (FIG. 12b, block (1220)) and the pallet load (PALO) is built by the palletizer (162) (FIG. 12b, block (1250)). If there are case units (CU) remaining, another (e.g., subsequent) pallet is planned to be included in the store order (FIG. 7, block (770)). Here, the pallet load generator (165, 165') updates the relationship between the store aisles (FIG. 12b, block (1240); FIG. 7, block (730)) so that all aisle combinations that include any aisle that has been completely consumed by previous pallets (e.g., aisles where all ordered case units have already been assigned to pallet loads) are removed and a list of updated aisle combinations (ALC) is generated (FIG. 7, block (730)). The iterative double loop (DRL) continues until there are no case units (CU) remaining that are not planned for any aisle of the store order (i.e., until all ordered case units have been assigned to pallet loads). The above pallet stack generator (165, 165') is configured to associate each of the store aisles with each other to perform at least one of minimizing the total number of pallet stacks within an order and minimizing the pallet per aisle ratio (RPA) (see FIG. 12b, block 1240, and also FIG. 7, block 730 described herein). It should be noted that, as described herein, the term "aisle" as used herein generally refers to both an order store aisle and a product group to which an integer value is assigned. As such, the order store aisles (e.g., physical locations within an order store) are related to each other by at least one of an aisle-to-aisle affinity characteristic and a product group type-to-product group type affinity characteristic.

FIG. 8 is a diagram showing a representative store order (800) planned by a pallet load generator (165, 165') employing the cluster aisle pallet load package distribution method described above. In this exemplary order (800), the volume of the case units in each aisle illustrated in FIG. 5 is shown as being contained in corresponding pallet loads (e.g., pallets 1 to 6), wherein each pallet load is sequentially planned (as described above) to have a volume (Vcomb) less than the maximum pallet volume (Vp). As can be seen in FIG. 8, the volume (V2) corresponding to the case units (CU) ordered for aisle 2 is divided (as described above) into pallet load 1 and pallet load 5 such that pallet load 1 is completely consumed by the case units ordered for aisle 2. It should be noted here that the last planned pallet load (e.g. pallet load 6) may have a smaller combined volume (Vcomb) than the previously planned pallet loads (e.g. pallet loads 1 to 5) because the last pallet load includes case units for aisles that were not included in the previous aisle combinations for the previously planned pallet loads 1 to 5, wherein the previously planned pallet loads are optimized for volume or weight, thereby affecting the optimization of the minimum number of pallets and/or the optimization of the pallet per aisle ratio (RPA).

According to the cluster aisle pallet load package distribution method, the generated pallet load(s) (PALO) are built by the palletizer (162) and shipped to the order counter (200) (FIG. 12b, block (1260)). The pallet load(s) (PALO) arrives at the order counter (200) from the warehouse (199). Referring to FIG. 2, the pallet load(s) (PALO) are typically received in the unloading dock area (222) of the order counter (200). Each of the pallet load(s) (PALO) includes products from various physical locations (e.g., aisles, corners, sections, etc.) of the order counter (200). For illustrative purposes, these physical locations will be referred to herein as aisles. It should be noted that although aisles 1 to 4 and aisles 11 to 14 are shown in FIG. 2, the ordering kiosk may have any suitable number of aisles. In a cluster aisle pallet load package distribution method, case units (CU) stored on a pallet load (PALO) are unloaded (e.g., manually or via automation such as an automated depalletizer similar to that described herein for palletizers (162, 162')) onto auxiliary pallet loads (PALO21, PALO22, PALO23) separated from the pallet load (PALO) (it should be understood that the three auxiliary pallet loads are shown for illustrative purposes and that there may be less than three auxiliary pallet loads), wherein each of the auxiliary pallet loads (PALO21, PALO22, PALO23) includes case units (CU) from separate single aisles. For example, the pallet load (PALO21) includes only case units (CU) assigned to aisle 1, the pallet load (PALO22) includes only case units (CU) assigned to aisle 3, and the pallet load (PALO 23) includes case units (CU) assigned to aisle 12. Only units (CU) are included. The auxiliary pallets (PALO21, PALO22, PALO23) are moved (e.g., manually and/or through automated transport) from the loading dock area (222) to the corresponding aisle assigned to the shopping area (224) of the ordering store (200), and the case units (CU) of the corresponding auxiliary pallet load (PALO21, PALO22, PALO23) are unloaded and placed on the corresponding store shelf (233) of the corresponding aisle assigned.

In a cluster aisle pallet loading package distribution method, a pallet load (PALO) can hold case units (CU) assigned to aisles that are spatially (e.g., far apart) from each other in the ordering store (200). As described above, unloading the case units (CU) assigned to the corresponding aisles to the corresponding auxiliary pallet loads (PALO21, PALO22, PALO23) is performed so that the pallet load (PALO) holding case units (CU) assigned to the aisles that are spatially (e.g., far apart) from each other has virtually no effect on the restocking/stocking of the store shelves (233). In this case, in a cluster aisle pallet load package distribution method, case units (CU) from different aisles can be assigned to a common pallet load (PALO) (regardless of aisle proximity) to maximize the number of full-size pallet loads (e.g., pallet loads having maximum pallet load dimensions and/or weight) and/or minimize the number of pallet loads (PALO) on a transport device moving the pallet loads (PALO) from the warehouse (199) to the order counter (200).

With reference now to FIGS. 1, 4, 5, 9, 12 and 13, a pallet according to order point-friendly characteristics for a mixed-mode cluster and adjacent-aisle pallet loading package distribution method will be described in more detail. The mixed-mode cluster and adjacent-aisle pallet loading package distribution method minimizes both (1) the number of pallets generated from a given set of products and (2) the average pallet per-aisle ratio (RPA), while minimizing the distance between shelf positions of case units assigned to each pallet. For illustrative purposes, aisle numbers that are numerically close to each other are also spatially close to each other (e.g., aisles 10 and 11 are close to each other and aisle 60 is distant from both aisles 10 and 11). Here, the cluster aisle pallet load package distribution method described above is modified so that pallet loads are planned (e.g., based on the continuity or proximity of one order aisle to another order aisle) and whereby at the order aisle (200), products on a common pallet are unloaded into aisles that are close to or adjacent to each other.

In the mixed mode cluster and adjacent aisle pallet loading package distribution method, orders are placed by the order kiosk (200) and at least one kiosk order affinity characteristic is determined in the manner described above with respect to blocks (1200, 1210) of FIG. 12b. Blocks (700A, 700B, 710, 720) of FIG. 13 are identical to the similarly numbered blocks in FIG. 7 described above. Therefore, the entire pallets are planned from aisles having case unit volumes greater than the pallet loading volume (Vp) and/or weights greater than the maximum pallet loading weight (Wmax), and the remaining case units ordered for those aisles are included in the aisle combination analysis (FIG. 13, blocks (700A, 700B, 710, and 720)) in the manner described above. The aisle combinations for the mixed mode cluster and adjacent aisle pallet loading package distribution method are also determined in the manner described above with respect to FIG. 7, block (730) (see also FIG. 12B, block (1220)), but the determined aisle combinations are ordered by a score (S) that describes the volume of case units ordered for any given aisle, the weight of case units ordered for any given aisle, and the proximity of the aisles included in any planned pallet (FIG. 13, block (1330)). For example, the score (S) can be expressed by the following equation:

(Formula 2)

can be determined by,

In the above Equation 2, minAisle and maxAisle are the minimum and maximum aisle numbers included in any given aisle combination, and d0 is a parameter greater than 0 that reflects the relative importance of the aisle spread/distance (e.g., store affinity) to the volume of case units within a pallet load. As can be seen from Equation 2, when the value of d0 is small, the aisle spread/distance is more important than the volume of case units within a pallet load, and when the value of d0 is large, the volume of case units within a pallet load is more important than the spread/distance between aisles assigned to the pallet load. The determined aisle combinations (see FIG. 7, block (730)) are weighted or assigned a score (S) and sorted based on the score (S) (FIG. 13, block (1330)). A repeatable double loop (DRL) is performed to plan the pallets in the manner described above with respect to FIG. 7, blocks (735, 740, 745, 750, 755, 760, 765, 770) (also see FIG. 12b, block (1230)) to optimize with respect to the minimum number of pallets and verify/confirm the optimization of the pallet per aisle ratio (RPA), but for each subsequent pallet, the updated aisle combinations are again scored (S) and sorted based on the score (S). The ordered case units are picked and planned pallet loads (PALOs) are built and shipped to the ordering store in the manner described above with respect to FIG. 12b, blocks (1240, 1250, and 1260).

FIG. 9 shows a representative example of planned pallet loads (e.g., pallets 1 through 7) determined by the mixed-mode cluster and adjacent-aisle pallet load package distribution method. In this representative example, the planned pallet loads are determined from an order having the aisles and corresponding case unit volumes illustrated in FIG. 2. As can be seen in FIG. 9, the first pallet load is planned from only a portion of the case unit volume (V2A) from aisle 2, and all other planned pallet loads in the store order have a volume (Vcomb) that is less than the expected volume (Vp) of the pallet load (as described above). According to the mixed-mode cluster and adjacent-aisle pallet load package distribution method, the planned pallet load 1 includes only the volume of the case units (V1) assigned to aisle 1. The planned pallet load 2 includes the volumes of the case units (V2B, V3) assigned to aisles 2 and 3. The planned pallet load 4 includes the volumes of case units V4 and V7 assigned to aisles 4 and 7, noting that although the planned pallet load 4 takes a break in the series of aisles, this break is not a major break since aisle 4 is only three aisles away from aisle 7, which complies with the objectives of the mixed mode cluster and adjacent aisle pallet load package distribution method. The planned pallet load 5 includes the volumes of case units V5 and V6 assigned to aisles 5 and 6. The planned pallet load 6 includes the volumes of case units V8 to V11 assigned to aisles 8 to 11. The planned pallet load 7 includes the volume of case units V12 assigned to aisle 12.

Also referring to FIG. 14, in some embodiments of the mixed mode cluster and adjacent aisle pallet load package distribution method, a maximum (or average) distance (MDmax), typically expressed as a difference between aisle numbers, between order case units (CUs) assigned to a given pallet may be specified by the ordering point (200). This embodiment of the mixed mode cluster and adjacent aisle pallet load package distribution method is the same as described above, except that aisle combinations that include aisles having an inter-aisle distance greater than the maximum distance (MDmax) are excluded/discarded prior to sorting the list of aisle combinations (see FIG. 14, block (1430)).

In another embodiment of the mixed-mode cluster and adjacent-aisle pallet load package distribution method as described herein with respect to FIG. 15, the pairwise relationship between aisles p and q can be specified by the ordering kiosk (200). The relationship between aisles p and q can be represented as an aisle affinity matrix A[p,q], where p and q belong to a set of all aisles that are in order. The aisle affinity matrix A[p,q] is diagonally symmetric such that A[p,q] equals A[q,p]. The values of the aisle affinity matrix A[p,q] should be substantially equal to or close to 1 for "kiosk friendly" aisles such that case units (CUs) for those aisles should be on the same (e.g., a single) pallet load. The values of the aisle affinity matrix A[p,q] should be substantially equal to or close to 0 for an "unfriendly" aisle, such that its case units (CUs) are separated from different pallet loads in the aisles (e.g., separating harsh products (e.g., laundry detergent) from foods (e.g., baby food) as noted above). The diagonal elements of the aisle affinity matrix A[p,q] should be equal to 1, such that for each p, A[p,p]=1, then any aisle is friendly to itself.

By employing pairwise relationships between aisles, the mixed-mode cluster and adjacent-aisle pallet loading package distribution methods remain as described above, but the score (S) is given by Equation 3 below for all {p,q} belonging to any given aisle combination.

(Formula 3)

As shown in Equation 3, the notation p is greater than or equal to 0 and is a multiplier representing the relative importance of affinity and pallet volume among aisles included in a given aisle combination (e.g., minimizing the total number of pallets). A smaller value of p indicates that aisle affinity is less important than minimizing the total number of pallets, while a larger value of p indicates that affinity is more important than minimizing the total number of pallets. In the manner described above (see FIG. 13), the determined aisle combinations are scored and the determined aisle combinations are sorted in descending order according to the scores, and starting from the first aisle combination in the sorted aisle combination list, pallet loading is planned for each sequential aisle combination until a successful pallet loading is planned, and then the minimum number of pallets is optimized to verify/confirm the optimization of the pallet rate per aisle (RPA).

With reference to FIGS. 1, 3, 5, 10, 11, 12 and 15, a pallet according to order store friendly characteristics for an adjacent-aisle pallet load package distribution method will be described in more detail. The adjacent-aisle pallet load package distribution method of pallet planning can be employed for warehouse customers who transport ordered pallets to store aisles for unloading case units directly from the ordered pallets onto store shelves. Here, as can be seen in FIG. 3, each ordered pallet load (PALOA, POLOA') is transported from one aisle to another along corresponding transport paths (300, 302) for unloading the case units. The transport paths (300, 302) move through the aisles in a sequential aisle sequence (e.g., pallet load (PALOA) moves through adjacent aisles 1 to 3 and pallet load (POLOA') moves through adjacent aisles 11 to 13).

In the adjacent-aisle pallet load package distribution method, the selection of consecutive or adjacent aisles is given priority when planning the pallet load, while the total number of pallets planned for any given order is minimized and excessive aisle splitting between the pallets is practically prevented. In cases where the aisles are split between two pallets, at most one aisle is split between the two pallets. A representative drawing of pallet loads planned for the "pure" adjacent-aisle pallet load package distribution method is illustrated in Fig. 10. As with other pallet load package distribution methods, aisles having a volume greater than a predetermined pallet load volume (Vp) (or a weight greater than the maximum weight (Wmax) of the pallet load) are selected and allocated to all/all pallets until the volume or weight remaining in the corresponding aisle becomes less than the volume (Vp) or weight (Wmax) (see Fig. 5 where the volume (V2) of aisle 2 is greater than the volume (Vp) of the pallet load). As can be seen in Figure 10, pallet load 1 is completely consumed by a portion (V2A) of the volume (V2) of aisle 2. As described herein, if the entire pallet load is planned from excess aisles, all remaining volumes and weights of the aisles in the order (e.g., the volumes and weights of the case units ordered for each corresponding aisle) are less than the volume (Vp) and weight (Wmax) of the pallet load. Because of this, each aisle has a quantity of case units expected to fit into a single pallet load, and in many cases will be combined with other case units from other aisles in a single pallet load to minimize the number of pallets and the pallet per aisle ratio (RPA).

The adjacent-aisle pallet load package distribution method minimizes the total number of pallets loaded into an order and the pallet load ratio per aisle (RPA) is minimized, but less so than assigning case units (CUs) to pallets in adjacent/adjacent aisle order (e.g., each available combination of order mezzanine aisles is determined more based on the contiguity or adjacency of the order mezzanine aisles within the available combination and less based on maximizing (either volume or weight) the pallet load. Planning pallet load according to the adjacent-aisle pallet load package distribution method may result in some aisles being split between pallets, but only by creating additional pallets where splits are avoided, thereby increasing the overall number of pallets planned for any given order.

If aisle splitting between pallet loads is not allowed, the total number of pallets can be increased. For example, FIG. 11 shows a store order planned with an adjacent-aisle pallet load package distribution method (e.g., as illustrated in FIG. 2 ) without splitting case units from the aisles between pallet loads (excluding any excess aisles, such as aisle 2, where a portion of the case units for each excess aisle are consumed by the entire pallet load and the remainder of the case units are distributed among the remaining pallet loads according to the adjacent-aisle pallet load package distribution method). The resulting order plan in FIG. 11 includes seven pallet loads, which is the same number of pallet loads as the mixed-mode cluster and adjacent-aisle pallet load package distribution methods, but one more pallet load than the pallet load of the cluster-aisle pallet load distribution method (note that these distribution methods examples are based on case unit orders for the aisles illustrated in FIG. 5 ). Also note here, as can be seen in Figure 11, that not splitting the aisles between the pallet loads will result in more pallets being created with case unit volumes lower than the maximum volume (Vp) of the corresponding pallet load, whereas in both the mixed-mode cluster and adjacent-aisle pallet load pallet distribution methods and the cluster-aisle pallet load package distribution methods (excluding the last planned pallet load), the case unit volumes are brought closer to the volume allowed for the pallet load (Vp).

Splitting of case units (CU) from some aisles is performed in pallet planning to increase average pallet volume and reduce or minimize the number of planned pallets while prioritizing close/adjacent aisle planning (e.g., store-friendly). Here, the adjacent aisle pallet loading package distribution method can be "modified" to employ threshold values (Vp0, Vp1), where

(Formula 4)

A relationship like this is formed.

The Vp0 and Vp1 values optimize the combination of pallet volumes (and minimizing the number of pallets) and the number of partition aisles. The Vp0 and Vp1 values should be reasonably close to Vp, for example:

(Formula 5)

and

(Formula 6)

A relationship like this is formed.

The Vp0 and Vp1 values are typically kept constant (e.g., do not change during the pallet planning iteration loops described herein), but may be adjusted for particular order profiles. For example, very large case units may warrant a decrease in Vp0 and Vp1 since it is more likely that some of their case units will not fit on any given pallet load, whereas small case units may warrant an increase in Vp0 and Vp1 since it is more likely that their case units will fit on any given pallet load.

In the adjacent aisle pallet loading package distribution method, orders are placed by ordering kiosk (200) and at least one kiosk order affinity characteristic is determined in the manner described above with respect to blocks (1200, 1210) of Fig. 12b. As described above, aisles having a volume greater than a predetermined pallet loading volume (Vp) (or a weight greater than a maximum weight (Wmax) of a pallet loading) are selected and assigned to all/all pallets. The number of pallets for an order (Np0) is given by the following equation 7

(Formula 7)

Based on the remaining case unit volume (Vrem) and weight (Wrem) and the expected product volume (Vp) and maximum weight (Wmax) in one pallet load according to the pallet load generator (165, 165') (Fig. 15, block (1500)).

The above pallet stack generator (165, 165') associates the aisles with each other (FIG. 12b, block (1220), which is a sequential aisle relationship in this example) and the determined aisle combinations disassemble the case unit array from the pallet stack (FIG. 12b, block (1230)). For example, the pallet load generator (165, 165') determines aisle combinations for the "next" pallet load (see FIG. 15, block 1505), where the "next" pallet load is the currently planned pallet load. Here, the aisles are selected sequentially (e.g., i, i+1, i+2 ...) and for each added aisle (see FIG. 15, block 1510), the cumulative case unit volume (Vcomb) and the cumulative pallet weight (Wcomb) are updated (see FIG. 15, block 1515). If the cumulative volume (Vcomb) is less than or equal to Vp0 and the cumulative weight (Wcomb) is less than or equal to Wmax (see FIG. 15, block 1520), the next aisle in the aisle sequence is added to the aisle combination (see FIG. 15, block 1510), thereby affecting the validation/verification of the pallet per aisle (RPA) optimization. If one of the cumulative volumes (Vcomb) has a Vp0 value Aisles are sequentially added to the aisle combination until the cumulative weight (Wcomb) exceeds the maximum pallet load weight (Wmax).

If one of the cumulative volumes (Vcomb) exceeds the value Vp0 and the cumulative weight (Wcomb) exceeds the maximum pallet load weight (Wmax), the remaining product volume (Vrem) and the remaining product weight (Wrem) are updated (Figure 15, block (1530)). An updated estimate of the number of pallets (Np1) for the order is determined by the pallet load generator (165, 165') in a similar manner as described above, but using the following equation 8

(Formula 8)

The updated values of Vrem and Wrem (i.e., the volume and weight remaining after the last passage selected in block (1510) of FIG. 15 of the first nested loop (RL1) nested within the full/wide loop illustrated in blocks (1500 to 1580 and 1590) of FIG. 15, including blocks (1510, 1515, 1520) of FIG. 15) are determined using the same.

If the total number of pallets (Np0) determined before selecting an aisle for the next pallet loading is equal to the updated number of pallets (Np1) (i.e., Np0 = Np1+1, where the number 1 represents the current pallet) (FIG. 15, block (1536)), the selection of aisles for the next pallet loading is stopped and pallet loading is planned from a combination of aisles that performs optimization with respect to the minimum number of pallets (FIG. 15, block (1565)).

When the number of updated pallets (Np1) increases (i.e., Np0 < Np1+1), an additional aisle in the aisle sequence is added to the aisle combination within the second nested loop (RL2) nested within the full/wide loop illustrated in blocks 1540, 1545, 1550, 1555, and 1560 of FIG. 15 (FIG. 15, block (1540)). When the next sequential aisle is added to the aisle combination (FIG. 15, block (1540)), the cumulative case unit volume (Vcomb) and the cumulative pallet weight (Wcomb) are updated (FIG. 15, block (1545)). The remaining volume (Vrem) and remaining weight (Wrem) of the case units in the order are also updated (FIG. 15, block (1550)). An updated estimate for the number of pallets (Np1) (updated) for the above order is determined by the pallet load generator (165, 165') in the manner described above (see Eq. 8) (see FIG. 15, block (1555)), but using the updated Vrem and Wrem values determined in block (1550) of FIG. 15, where the following conditions (Eqs. 9 to 11):

(Formula 9)

(Formula 10)

or

(Formula 11)

If any of the conditions are not met, a recursive loop (RL2) is repeated to add additional passages to the passage combination.

If any one of the above conditions (Equations 9 to 11) is satisfied, the selection of aisles for the next pallet loading is stopped and pallet loading is planned from the aisle combination (Fig. 15, block (1565)) to perform optimization with respect to the minimum number of pallets.

When a pallet load is planned (FIG. 15, block (1565)), products not planned from an aisle combination (e.g., aisle 6 divided into case unit volumes (V6A, V6B) and aisle 12 divided into case unit volumes (V12A, V12B)) are added to the remaining products in the order by the pallet load generator (165, 165') (FIG. 15, block 1570). The pallet load generator (165, 165') adds the planned pallet load (from FIG. 15, block (1565)) to an output list of pallet loads that influences the construction of the pallet loads in the output list (FIG. 15, block (1575)). The pallet load generator (165, 165') determines if there are any case units (CU) remaining in the order (FIG. 15, block 1580) and again verifies/confirms the optimization of the pallet per aisle ratio (RPA). If there are no more case units, the pallet load planning for the order is stopped (FIG. 15, block 1585) and the pallet loads (PALOA, PALOA') are built and shipped to the order point (200) in the manner described above with respect to FIG. 12, blocks (1240, 1250 and 1260). If there are any case units (CU) remaining in the order, the number of pallets in the order is updated (FIG. 15, block 1590) and another pallet is planned for the order in the manner described above to minimize the number of pallets.

In the above adjacent aisle pallet load package distribution method, making the volume of the selected case units greater than the first critical volume (Vp0) can increase the probability that at least one aisle will not be completely packed with the currently planned pallet load, thereby causing a portion of at least one aisle to overflow with the planned next pallet load. Overflow of case units from one pallet load to the next subsequent pallet load can increase the value of the pallet per aisle (RPA) and decrease the aisle adjacency (e.g., the overall store friendliness of the ordered pallet load). The values of Vp0 and Vp1 can be adjusted to reflect the importance of minimizing the total number of pallets with respect to the pallet per aisle (RPA) as noted above. Higher values of both Vp0 and Vp1 (e.g., closer to Vp) can decrease the expected number of pallets, and lower values of both Vp0 and Vp1 can decrease the probability of aisle splitting between pallets (but can increase the expected number of pallets).

Fig. 11 shows a pallet load of an order planned with the adjacent-aisle pallet load package distribution method described above. As noted above, the volumes depicted in Fig. 11 are the same volumes corresponding to the aisles depicted in Fig. 5. According to the adjacent-aisle pallet load package distribution method, a part (V2A) of the volume (V2) of aisle 2 consumes the entire/all pallet load (e.g., pallet load 1), while the remaining volume (V2B) of aisle 2 is taken into account in the pallet planning according to Figs. 12 and 15 (as described above). It should be noted that the volume (V6) of aisle 6 is divided between pallet loads 4 and 5, while the volume (V12) of aisle 12 is divided between pallet loads 6 and 7. The remaining volumes (V1, V3, V4, V5, V7-V11) of aisles (1, 3, 4, 5, and 7-11) and the remaining volume of aisle 2 are assigned to only one corresponding pallet load, each of the pallets having a sequential aisle order assigned to the pallet load. In this example, the total number of pallet loads is 7 (as in FIG. 10 , the pallet loads are planned as "pure" aisle adjacent without employing thresholds (Vp0, Vp1) and double-nested loops (RL1, RL2); however, the last pallet load (pallet load 7) in FIG. 11 has a relatively smaller volume than the last pallet load in FIG. 10 and can be placed on other pallet loads in the order, which reduces the floor space required to transport the ordered pallet loads. It is important to note that a “modified” adjacent-aisle pallet load package distribution method (which allows for the aisle case unit volumes to be divided between the pallet loads) will typically result in a smaller planned number of pallet loads than a “pure” adjacent-aisle pallet load package distribution method (which does not allow for the aisle case unit volumes to be divided between the pallet loads).

Referring now to FIGS. 1 to 4 and FIG. 16, a method of constructing a pallet load (PALO) according to one or more of a cluster aisle pallet load package distribution method, a mixed mode cluster and adjacent aisle pallet load package distribution method, and an adjacent aisle pallet load package distribution method will be described. Here, packages are arranged on a pallet to form a pallet load (PALO) (FIG. 16, block (1600)) (see FIG. 1). Individual case units (CU) are provided to an automated palletizer for forming the pallet load (PALO) from a storage array (130) as described herein, wherein the pallet load (PALO) comprises more than one composite layer (L1-Ln) of case units (CU). A pallet stack (PALO) is formed by case units (CU) arranged in the pallet stack (PALO) to embody at least one pallet for an ordering point friendly characteristic (166, 166') (FIG. 16, block (1610)) for a pre-determined pallet loading package distribution method at the ordering point (200). As described herein, the at least one pallet for the ordering point friendly characteristic (166, 166') is for at least a cluster-aisle pallet loading package distribution method, a mixed-mode cluster and adjacent-aisle pallet loading package distribution method, and an adjacent-aisle pallet loading package distribution method at the ordering point.

According to one or more embodiments of the present disclosure, a material handling system for handling packages and placing the packages on pallets destined for an ordering point, the material handling system comprising: a storage array having storage spaces for holding packages therein; an automated package transfer system communicatively connected to the storage array for storing packages within the storage spaces of the storage array and for retrieving packages from the storage spaces of the storage array; an automated palletizer for placing packages on pallets to form a pallet load, the automated palletizer being communicatively connected to the automated package transfer system, the automated package transfer system being configured to provide individual packages from the storage array to the automated palletizer to form the pallet load, the pallet load including more than one composite package layer; and a controller operably connected to said automated palletizer, wherein the controller is programmed with a pallet load generator having at least one pallet for a predetermined pallet load package distribution method at said order counter, said pallet load generator being configured to cause a pallet load to be formed by the automated palletizer of packages arranged within said pallet load to specify at least one pallet for the order counter friendly characteristic;

According to one or more embodiments of the present disclosure, at least one pallet for order kiosk friendly specification is for at least a cluster aisle pallet load package distribution method, a mixed mode cluster and adjacent aisle pallet load package distribution method, and an adjacent aisle pallet load package distribution method at the order kiosk.

According to one or more embodiments of the present disclosure, at least one pallet for an order-to-shop friendly characteristic is notified by an iterative two-loop determination where at least one loop relates order-to-shop aisles to each other.

According to one or more embodiments of the present disclosure, within the determination of at least one loop, the ordering aisles are related to each other by at least one of an aisle-to-aisle affinity characteristic and a product group type-to-product group type affinity characteristic.

According to one or more embodiments of the present disclosure, the aisle-to-aisle affinity characteristic is the distance separating one ordering kiosk aisle from another ordering kiosk aisle, or the proximity or proximity of one ordering kiosk aisle to another ordering kiosk.

According to one or more embodiments of the present disclosure, at least one pallet for which an order-to-shop friendly characteristic is provided is notified by an iterative dual-loop determination of at least one loop to determine available order-to-shop aisle combinations to disorganize the arrangement of packages within the pallet load.

According to one or more embodiments of the present disclosure, each of the available order kiosk aisle combinations is determined based on a maximization of the pallet load, or a combined maximization of the pallet load and the proximity or adjacency of the aisles within the available order kiosk aisle combination, wherein the maximization of the pallet load is weighted more heavily than the proximity or adjacency of the aisles.

According to one or more embodiments of the present disclosure, each of the available order aisle combinations is determined more based on proximity or adjacency of the order aisles within the available order aisle combination and less based on maximizing the pallet load.

According to one or more embodiments of the present disclosure, the pallet load generator disassembles the pallet load according to at least one pallet for a store friendly characteristic such that the pallet load is maximized with respect to at least one of a maximum pallet load volume and a maximum pallet load weight.

According to one or more embodiments of the present disclosure, the pallet load generator disassembles the pallet load according to at least one pallet for order-point friendly characteristics such that the pallet load has a maximum number of packages from a minimum number of order-point aisles.

According to one or more embodiments of the present disclosure, the pallet load generator disassembles the pallet load according to at least one pallet for order kiosk friendly characteristic to generate a minimum number of pallet loads for each order kiosk.

According to one or more embodiments of the present disclosure, the pallet load generator disassembles the pallet load according to at least one pallet for an order counter friendly characteristic such that, for each pallet load scheduled for the order counter, the packages forming the pallet load represent a minimum number of order counter aisles.

According to one or more embodiments of the present disclosure, the pallet load generator disassembles, for each pallet load scheduled for the order kiosk, the pallet load according to at least one pallet for an order kiosk friendly characteristic such that the disassembled pallet load represents a minimum number of order kiosk aisles.

According to one or more embodiments of the present disclosure, the pallet load generator is configured to sequentially dismantle each pallet load via an iterative double-loop determination that notifies at least one pallet of an order-standby friendly characteristic.

According to one or more embodiments of the present disclosure, at least one pallet for which an order-to-shop friendly characteristic is provided is notified by a double-nested loop determination that at least one loop associates order-to-shop aisles with each other or determines available order-to-shop aisle combinations to disorganize the arrangement of packages within the pallet load.

According to one or more embodiments of the present disclosure, an automated palletizer comprises an automated package pick device capable of moving packages from a package deposit section onto a pallet to form a pallet load from said packages, said pallet load comprising more than one composite package layer; a controller operably connected to the automated palletizer, said controller being programmed with a pallet load generator having at least one pallet for order-store friendly characteristics for a predetermined pallet load package dispensing method at said order-store, said pallet load generator causing said pallet load to be formed by the automated palletizer of packages arranged within said pallet load to form at least one pallet for order-store friendly characteristics.

According to one or more embodiments of the present disclosure, at least one pallet for order kiosk friendly characteristics is for at least a cluster aisle pallet load package distribution method, a mixed mode cluster and adjacent aisle pallet load package distribution method, and an adjacent aisle pallet load package distribution method at the order kiosk.

According to one or more embodiments of the present disclosure, at least one pallet for an order-to-shop friendly characteristic is notified by an iterative two-loop determination where at least one loop relates order-to-shop aisles to each other.

According to one or more embodiments of the present disclosure, within the determination of at least one loop, the ordering aisles are related to each other by at least one of an aisle-to-aisle affinity characteristic and a product group type-to-product group type affinity characteristic.

According to one or more embodiments of the present disclosure, the aisle-to-aisle affinity characteristic is the distance separating one ordering aisle from another ordering aisle, or the proximity or proximity of one ordering aisle to another ordering aisle.

According to one or more embodiments of the present disclosure, at least one pallet for which an order-to-shop friendly characteristic is provided is notified by an iterative dual-loop determination of at least one loop to determine available order-to-shop aisle combinations to disorganize the arrangement of packages within the pallet load.

According to one or more embodiments of the present disclosure, each of the available order kiosk aisle combinations is determined based on a maximization of pallet loading, or a combined maximization of pallet loading and proximity or adjacency of aisles within the available order kiosk aisle combination, wherein the maximization of pallet loading is weighted more heavily than the proximity or adjacency of the aisles.

According to one or more embodiments of the present disclosure, each of the available order aisle combinations is determined more based on proximity or adjacency of the order aisles within the available order aisle combination and less based on maximizing the pallet load.

According to one or more embodiments of the present disclosure, the pallet load generator disassembles the pallet load according to at least one pallet for a store friendly characteristic such that the pallet load is maximized with respect to at least one of a maximum pallet load volume and a maximum pallet load weight.

According to one or more embodiments of the present disclosure, the pallet load generator disassembles the pallet load according to at least one pallet for order-point friendly characteristics such that the pallet load has a maximum number of packages from a minimum number of order-point aisles.

According to one or more embodiments of the present disclosure, the pallet load generator disassembles the pallet load according to at least one pallet for order kiosk friendly characteristic to generate a minimum number of pallet loads for each order kiosk.

According to one or more embodiments of the present disclosure, the pallet load generator disassembles the pallet load according to at least one pallet for order shop friendly characteristics such that, for each pallet load scheduled for the order shop, the packages forming the pallet load represent a minimum number of order shop aisles.

According to one or more embodiments of the present disclosure, the pallet load generator disassembles, for each pallet load scheduled for the order kiosk, the pallet load according to at least one pallet for an order kiosk friendly characteristic such that the disassembled pallet load represents a minimum number of order kiosk aisles.

According to one or more embodiments of the present disclosure, the pallet load generator is configured to sequentially dismantle each pallet load via an iterative double-loop determination that notifies at least one pallet of an order point-friendly characteristic.

According to one or more embodiments of the present disclosure, at least one pallet for which an order-to-shop friendly characteristic is provided is notified by a double-nested loop determination that at least one loop associates order-to-shop aisles with each other or determines available order-to-shop aisle combinations to disorganize the arrangement of packages within the pallet load.

According to one or more embodiments of the present disclosure, a method of constructing a pallet load comprises the steps of arranging packages on a pallet to form a pallet load, individual packages being provided from a storage array to form the pallet load, the pallet load comprising more than one composite package layer, the pallet load being formed by the packages arranged within the pallet load to embody at least one pallet having order-point friendly characteristics for a predetermined pallet load package distribution method at an order-point.

According to one or more embodiments of the present disclosure, at least one pallet for order kiosk friendly characteristics is for at least a cluster aisle pallet load package distribution method, a mixed mode cluster and adjacent aisle pallet load package distribution method, and an adjacent aisle pallet load package distribution method at the order kiosk.

According to one or more embodiments of the present disclosure, at least one pallet for an order-to-shop friendly characteristic is notified by an iterative two-loop determination where at least one loop relates order-to-shop aisles to each other.

According to one or more embodiments of the present disclosure, within the determination of at least one loop, the ordering aisles are related to each other by at least one of an aisle-to-aisle affinity characteristic and a product group type-to-product group type affinity characteristic.

According to one or more embodiments of the present disclosure, the aisle-to-aisle affinity characteristic is the distance separating one ordering kiosk aisle from another ordering kiosk aisle, or the proximity or proximity of one ordering kiosk aisle to another ordering kiosk.

According to one or more embodiments of the present disclosure, at least one pallet for which an order-to-shop friendly characteristic is provided is notified by an iterative dual-loop determination of at least one loop to determine available order-to-shop aisle combinations to disorganize the arrangement of packages within the pallet load.

According to one or more embodiments of the present disclosure, each of the available order kiosk aisle combinations is determined based on a maximization of pallet loading, or a combined maximization of pallet loading and proximity or adjacency of aisles within the available order kiosk aisle combination, wherein the maximization of pallet loading is weighted more heavily than the proximity or adjacency of the aisles.

According to one or more embodiments of the present disclosure, each of the available order aisle combinations is determined more based on proximity or adjacency of the order aisles within the available order aisle combination and less based on maximizing the pallet load.

According to one or more embodiments of the present disclosure, the pallet load is dismantled according to at least one pallet for a store friendly characteristic such that the pallet load is maximized with respect to at least one of a maximum pallet load volume and a maximum pallet load weight.

According to one or more embodiments of the present disclosure, the pallet load is dismantled according to at least one pallet for order-point friendly characteristics such that the pallet load carries a maximum number of packages from a minimum number of order-point aisles.

According to one or more embodiments of the present disclosure, the pallet stack is disassembled according to at least one pallet for ordering point friendly characteristics to produce a minimum number of pallet stacks for each ordering point.

According to one or more embodiments of the present disclosure, the pallet load is dismantled into at least one pallet for order counter friendly characteristics such that, for each pallet load scheduled for the order counter, the packages forming the pallet load represent a minimum number of order counter aisles.

According to one or more embodiments of the present disclosure, the pallet load is dismantled according to at least one pallet for order counter friendly characteristic such that, for each pallet load destined for the order counter, the dismantled pallet load represents a minimum number of order counter aisles.

According to one or more embodiments of the present disclosure, each pallet load is sequentially dismantled via an iterative, double-loop determination that notifies at least one pallet of a store-friendly characteristic.

According to one or more embodiments of the present disclosure, at least one pallet for which an order-to-shop friendly characteristic is provided is notified by a double-nested loop determination that at least one loop associates order-to-shop aisles with each other or determines available order-to-shop aisle combinations to disorganize the arrangement of packages within the pallet load.

According to one or more embodiments of the present disclosure, a pallet load comprises more than one composite package layer stacked on a pallet base, wherein the more than one composite package layer is formed by packages arranged within the pallet load such that at least one pallet embodies order-point friendly characteristics for a predetermined pallet load package distribution method at an order-point.

According to one or more embodiments of the present disclosure, at least one pallet for order kiosk friendly characteristics is for at least a cluster aisle pallet load package distribution method, a mixed mode cluster and adjacent aisle pallet load package distribution method, and an adjacent aisle pallet load package distribution method at the order kiosk.

According to one or more embodiments of the present disclosure, at least one pallet for an order-to-shop friendly characteristic is notified by an iterative two-loop determination where at least one loop relates order-to-shop aisles to each other.

According to one or more embodiments of the present disclosure, within at least one loop of determination, the ordering aisles are related to each other by at least one of an aisle-to-aisle affinity characteristic and a product group type-to-product group type affinity characteristic.

According to one or more embodiments of the present disclosure, the aisle-to-aisle affinity characteristic is the distance separating one ordering kiosk aisle from another ordering kiosk aisle, or the proximity or proximity of one ordering kiosk aisle to another ordering kiosk.

According to one or more embodiments of the present disclosure, at least one pallet for which an order-to-shop friendly characteristic is provided is notified by an iterative dual-loop determination of at least one loop to determine available order-to-shop aisle combinations to disorganize the arrangement of packages within the pallet load.

According to one or more embodiments of the present disclosure, each of the available order kiosk aisle combinations is determined based on a maximization of pallet loading, or a combined maximization of pallet loading and proximity or adjacency of aisles within the available order kiosk aisle combination, wherein the maximization of pallet loading is weighted more heavily than the proximity or adjacency of the aisles.

According to one or more embodiments of the present disclosure, each of the available order aisle combinations is determined more based on proximity or adjacency of the order aisles within the available order aisle combination and less based on maximizing pallet loading.

According to one or more embodiments of the present disclosure, the pallet load is dismantled according to at least one pallet for a store friendly characteristic such that the pallet load is maximized with respect to at least one of a maximum pallet load volume and a maximum pallet load weight.

According to one or more embodiments of the present disclosure, the pallet load is dismantled according to at least one pallet for order-point friendly characteristics such that the pallet load carries a maximum number of packages from a minimum number of order-point aisles.

According to one or more embodiments of the present disclosure, the pallet stack is disassembled according to at least one pallet for ordering point friendly characteristics to produce a minimum number of pallet stacks for each ordering point.

According to one or more embodiments of the present disclosure, the pallet load is dismantled into at least one pallet for order counter friendly characteristics such that, for each pallet load scheduled for the order counter, the packages forming the pallet load represent a minimum number of order counter aisles.

According to one or more embodiments of the present disclosure, the pallet load is dismantled according to at least one pallet for order counter friendly characteristic such that, for each pallet load destined for the order counter, the dismantled pallet load represents a minimum number of order counter aisles.

In accordance with one or more embodiments of the present disclosure, each pallet load is sequentially dismantled via repeated double-loop determinations that notify at least one pallet of an order-to-shop characteristic according to one or more embodiments of the present disclosure, and at least one pallet of an order-to-shop friendly characteristic is notified by double-nested loop determinations that dismantle the arrangement of packages within the pallet load by associating order-to-shop aisles with each other or determining available order-to-shop aisle combinations. It should be understood that the foregoing description is illustrative of embodiments of the present disclosure. Various alternatives and modifications may be devised by those skilled in the art without departing from the embodiments of the present disclosure. Accordingly, the embodiments of the present disclosure are intended to cover all such alternatives, modifications and variations that fall within the scope of any claims appended hereto. Furthermore, the mere fact that different features are recited in different dependent or independent claims does not imply that a combination of such features cannot be used to advantage, and such combinations are within the scope of the embodiments of the present disclosure.

Claims (60)

A material handling system for handling packages and placing said packages on pallets scheduled for an ordering point, said material handling system comprising:
A storage array having storage spaces for holding packages inside;
An automated package transfer system communicatively connected to the storage array for storing packages within storage spaces of the storage array and retrieving packages from storage spaces of the storage array;
An automated palletizer for placing packages on a pallet to form a pallet load, wherein the automated palletizer is communicatively connected to the automated package transfer system, the automated package transfer system is configured to provide individual packages from the storage array to the automated palletizer to form the pallet load, the pallet load comprising more than one composite package layer; and
A controller operably connected to said automated palletizer, wherein the controller is programmed with a pallet load generator having at least one pallet for an order counter friendly specification for a predetermined method of distributing palletized packages at said order counter, wherein the pallet load generator is configured to cause the automated palletizer to form a pallet load of packages arranged within said pallet load so as to specify at least one pallet for the order counter friendly specification;
A material handling system, including: In the first paragraph,
A material handling system, wherein at least one pallet for the order kiosk friendly specification is at least for a cluster aisle pallet loading package distribution method, a mixed mode cluster and adjacent aisle pallet loading package distribution method, and an adjacent aisle pallet loading package distribution method at the order kiosk. In the first paragraph,
A material handling system, wherein at least one pallet for which an order-to-store friendly characteristic is provided is notified by a repetitive double-loop determination that at least one loop relates order-to-store aisles to each other. In the third paragraph,
A material handling system, wherein within the determination of at least one of the above loops, the ordering aisles are related to each other by at least one of an aisle-to-aisle affinity characteristic and a product group type-to-product group type affinity characteristic. In paragraph 4,
A materials handling system wherein the aisle-to-aisle affinity characteristic is the distance separating one ordering point aisle from another ordering point aisle, or the proximity or adjacency of one ordering point aisle to another ordering point. In the first paragraph,
A material handling system wherein at least one pallet for which an order-to-shop friendly characteristic is provided is notified by an iterative dual-loop determination of at least one loop to determine available order-to-shop aisle combinations to disassemble the arrangement of packages within said pallet load. In Article 6,
Each of the above available ordering point aisle combinations is:
Maximizing the pallet loading above, or
Maximizing the combined proximity or adjacency of aisles within the above pallet stacking and the available ordering point aisle combinations.
is determined based on,
A material handling system in which maximizing the pallet loading is given greater weight than the proximity or adjacency of the aisles. In Article 6,
A material handling system, wherein each of the available order aisle combinations is determined more based on the proximity or adjacency of the order aisles within the available order aisle combinations and less based on maximizing the pallet load. In the first paragraph,
A material handling system wherein the pallet stack generator disassembles the pallet stack according to at least one pallet for order point friendly characteristics such that the pallet stack is maximized for at least one of a maximum pallet stack volume and a maximum pallet stack weight. In the first paragraph,
A material handling system wherein the pallet stack generator disassembles the pallet stack into at least one pallet according to order-point friendly characteristics such that the pallet stack has a maximum number of packages from a minimum number of order-point aisles. In the first paragraph,
A material handling system wherein the pallet stack generator disassembles the pallet stack according to at least one pallet for order stand friendly characteristics to generate a minimum number of pallet stacks for each order stand. In the first paragraph,
A material handling system wherein the pallet stack generator disassembles the pallet stack according to at least one pallet for order-stand friendly characteristics such that, for each pallet stack scheduled for the order-stand, the packages forming the pallet stack represent a minimum number of order-stand aisles. In the first paragraph,
A material handling system wherein the pallet stack generator disassembles the pallet stack according to at least one pallet for order-store friendly characteristics such that, for each pallet stack scheduled for the order-store, the disassembled pallet stack represents a minimum number of order-store aisles. In the first paragraph,
A material handling system wherein the pallet stack generator is configured to sequentially disassemble each pallet stack via a repetitive double-loop decision that notifies at least one pallet of an order point-friendly characteristic. In the first paragraph,
A material handling system wherein at least one pallet for which an order-to-shop friendly characteristic is provided is notified by a double-nested loop determination that at least one loop relates order-to-shop aisles to each other or determines available order-to-shop aisle combinations to disorganize the arrangement of packages within said pallet load. As an automated palletizer,
The above automated palletizer,
An automated package pick device capable of moving packages from a package deposit section onto a pallet to form a pallet load from said packages, said pallet load comprising more than one composite package layer; and
A controller operably connected to the above automated palletizer
Including,
An automated palletizer wherein said controller is programmed with a pallet load generator having at least one pallet for order counter friendly characteristics for a predetermined method of distributing palletized packages at said order counter, said pallet load generator causes said pallet load to be formed by an automated palletizer of packages arranged within said pallet load, thereby specifying at least one pallet for order counter friendly characteristics. In Article 16,
An automated palletizer, wherein at least one pallet for order point friendly characteristics is for at least a cluster aisle pallet loading package distribution method, a mixed mode cluster and adjacent aisle pallet loading package distribution method, and an adjacent aisle pallet loading package distribution method at said order point. In Article 16,
An automated palletizer, wherein at least one pallet having an order-to-shop friendly characteristic is notified by a repetitive double-loop determination that at least one loop relates order-to-shop aisles to each other. In Article 18,
An automated palletizer, wherein within the determination of at least one of said loops, the ordering aisles are related to each other by at least one of an aisle-to-aisle affinity characteristic and a product group type-to-product group type affinity characteristic. In Article 19,
The aisle-to-aisle affinity characteristic is the distance separating one order aisle from another order aisle, or the proximity or adjacency of one order aisle to another order aisle, an automated palletizer. In Article 16,
An automated palletizer wherein at least one pallet for which an order-to-shop friendly characteristic is provided is notified by an iterative dual-loop determination of at least one loop to de-arrange the packages within said pallet stack by determining available order-to-shop aisle combinations. In Article 21,
Each of the above available ordering point aisle combinations is:
Maximize pallet loading, or
Combined maximization of pallet stacking and proximity or proximity of aisles within the available ordering point aisle combinations.
is determined based on,
An automated palletizer wherein maximizing the pallet loading is given greater weight than the proximity or adjacency of the aisles. In Article 21,
An automated palletizer, wherein each of said available order aisle combinations is determined more based on the proximity or adjacency of the order aisles within the available order aisle combinations and less based on maximizing the pallet load. In Article 16,
An automated palletizer wherein the pallet stack generator disassembles the pallet stack according to at least one pallet for order point friendly characteristics such that the pallet stack is maximized for at least one of maximum pallet stack volume and maximum pallet stack weight. In Article 16,
An automated palletizer wherein the pallet stack generator disassembles the pallet stack into at least one pallet according to order-point friendly characteristics such that the pallet stack has a maximum number of packages from a minimum number of order-point aisles. In Article 16,
An automated palletizer wherein the pallet stack generator disassembles the pallet stack according to at least one pallet for order-point friendly characteristics to generate a minimum number of pallet stacks for each order-point. In Article 16,
An automated palletizer wherein the pallet stack generator disassembles the pallet stack into at least one pallet for order-place friendly characteristics such that, for each pallet stack scheduled for the order-place, the packages forming the pallet stack represent a minimum number of order-place aisles. In Article 16,
An automated palletizer wherein the pallet stack generator disassembles the pallet stack according to at least one pallet for order-store friendly characteristics such that, for each pallet stack scheduled for the order-store, the disassembled pallet stack represents a minimum number of order-store aisles. In Article 16,
An automated palletizer wherein the pallet stack generator is configured to sequentially disassemble each pallet stack via a repetitive double-loop decision that notifies at least one pallet of an order-point-friendly characteristic. In Article 16,
An automated palletizer wherein at least one pallet having an order-to-shop friendly characteristic is notified by a double nested loop determination that at least one loop relates order-to-shop aisles to each other or determines available order-to-shop aisle combinations to disassemble the arrangement of packages within said pallet load. As a method of constructing a pallet stack,
A method of constructing a pallet stack, the method comprising the steps of: arranging packages on a pallet to form a pallet stack, individual packages being provided from a storage array to form the pallet stack, the pallet stack comprising more than one composite package layer, the pallet stack being formed by the packages arranged within the pallet stack to embody at least one pallet having order-stand friendly characteristics for a predetermined pallet load package distribution method at an order-stand. In Article 31,
A method of constructing a pallet stack, wherein at least one pallet having an ordering point friendly characteristic is for at least a cluster aisle pallet stacking package distribution method, a mixed mode cluster and adjacent aisle pallet stacking package distribution method, and an adjacent aisle pallet stacking package distribution method at said ordering point. In Article 31,
A method of constructing a pallet stack, wherein at least one pallet having an order-to-store friendly characteristic is notified by an iterative double-loop determination that at least one loop relates order-to-store aisles to each other. In Article 33,
A method of constructing a pallet stack, wherein within the determination of at least one of the above loops, the ordering point aisles are related to each other by at least one of an aisle-to-aisle affinity characteristic and a product group type-to-product group type affinity characteristic. In Article 34,
A method of constructing a pallet stacking, wherein the aisle-to-aisle affinity characteristic is the distance separating one ordering point aisle from another ordering point aisle, or the proximity or adjacency of one ordering point aisle to another ordering point. In Article 31,
A method of constructing a pallet stack, wherein at least one pallet having an order-to-shop friendly characteristic is informed by an iterative dual-loop determination of at least one loop to determine available order-to-shop aisle combinations to disassemble the arrangement of packages within said pallet stack. In Article 36,
Each of the available ordering store aisle combinations is:
Maximize pallet loading, or
Combined maximization of pallet stacking and proximity or proximity of aisles within the available ordering point aisle combinations.
is determined based on,
A method of constructing pallet stacking, wherein maximizing the pallet stacking is given greater weight than the proximity or adjacency of the aisles. In Article 36,
A method of constructing a pallet stack, wherein each of the available ordering aisle combinations is determined more based on the proximity or adjacency of the ordering aisles within the available ordering aisle combinations and less based on maximizing the pallet stack. In Article 31,
A method of constructing a pallet stack, wherein the pallet stack is dismantled according to at least one pallet for order point friendly characteristics such that the pallet stack is maximized for at least one of a maximum pallet load volume and a maximum pallet load weight. In Article 31,
A method of constructing a pallet stack, wherein the pallet stack is dismantled into at least one pallet according to order-point friendly characteristics such that the pallet stack carries a maximum number of packages from a minimum number of order-point aisles. In Article 31,
A method of constructing a pallet stack, wherein the pallet stack is dismantled according to at least one pallet for ordering point friendly characteristics to create a minimum number of pallet stacks for each ordering point. In Article 31,
A method of constructing a pallet stack, wherein for each pallet stack scheduled for said order counter, the packages forming said pallet stack are dismantled into at least one pallet according to order counter friendly characteristics such that the packages present a minimum number of order counter aisles. In Article 31,
A method of constructing a pallet stack, wherein the pallet stack is dismantled according to at least one pallet for order-store friendly characteristics such that, for each pallet stack scheduled for the order-store, the dismantled pallet stack represents a minimum number of order-store aisles. In Article 31,
A method of constructing a pallet stack, wherein each pallet stack is sequentially dismantled via an iterative double-loop decision that notifies at least one pallet of its order-point-friendly characteristics. In Article 31,
A method of constructing a pallet stack, wherein at least one pallet having an order-to-shop friendly characteristic is notified by a double-nested loop determination that at least one loop relates order-to-shop aisles to each other or determines available order-to-shop aisle combinations to disassemble the arrangement of packages within said pallet stack. As a pallet loader,
A pallet stack comprising at least one composite package layer stacked on a pallet base, wherein the at least one composite package layer is formed by packages arranged within the pallet stack to embody at least one pallet having order-place friendly characteristics for a predetermined pallet stack package distribution method at an order-place. In Article 46,
At least one pallet for order point friendly characteristics is for at least a cluster aisle pallet loading package distribution method, a mixed mode cluster and adjacent aisle pallet loading package distribution method, and an adjacent aisle pallet loading package distribution method at said order point. In Article 46,
Pallet stacking, where at least one pallet for which the order-to-store friendly characteristic is present is notified by a repetitive double-loop determination that at least one loop relates order-to-store aisles to each other. In Article 48,
Within at least one loop of decision, the ordering aisles are related to each other by at least one of an aisle-to-aisle affinity characteristic and a product group type-to-product group type affinity characteristic, pallet loading. In Article 49,
The aisle-to-aisle affinity characteristic is the distance separating one ordering aisle from another ordering aisle, or the proximity or adjacency of one ordering aisle to another ordering aisle, for pallet loading. In Article 46,
A pallet stack wherein at least one pallet having an order-to-shop friendly characteristic is notified by an iterative dual-loop determination of at least one loop to determine available order-to-shop aisle combinations to disassemble the arrangement of packages within said pallet stack. In Article 51,
Each of the above available ordering point aisle combinations is:
Maximize pallet loading, or
Pallet loading is determined based on a combined maximization of the proximity or adjacency of aisles within said available ordering point aisle combination and said maximization of pallet loading is weighted more heavily than the proximity or adjacency of the aisles. In Article 51,
Each of the above available order aisle combinations is determined based more on the proximity or adjacency of the order aisles within the available order aisle combinations and less on maximizing pallet loading, wherein the pallet loading is determined. In Article 46,
The above pallet stack is dismantled according to at least one pallet for order point friendly characteristics such that the pallet stack is maximized for at least one of the maximum pallet load volume and the maximum pallet load weight. In Article 46,
The above pallet stack is dismantled into at least one pallet according to the order counter friendly characteristics such that the pallet stack carries the maximum number of packages from the minimum number of order counter aisles. In Article 46,
The above pallet stack is disassembled according to at least one pallet for ordering point friendly characteristics to produce a minimum number of pallet stacks for each ordering point. In Article 46,
The above pallet stacking is a pallet stacking wherein, for each pallet stack scheduled for the above order counter, the packages forming the pallet stack are disassembled into at least one pallet according to the order counter friendly characteristics such that the packages present a minimum number of order counter aisles. In Article 46,
The above pallet stacking is dismantled according to at least one pallet for the order counter friendly characteristic such that for each pallet stack scheduled to the order counter, the dismantled pallet stack represents the minimum number of order counter aisles. In Article 46,
Pallet loads are sequentially dismantled via an iterative double-loop decision that notifies at least one pallet of its order-store-friendly characteristics. In Article 46,
A pallet stack wherein at least one pallet having an order-to-shop friendly characteristic is notified by a double-nested loop determination that at least one loop relates order-to-shop aisles to each other or determines available order-to-shop aisle combinations to disorganize the arrangement of packages within said pallet stack.