CN106203740A - A kind of warehouse logistics vehicle dispatching method and system - Google Patents

Abstract

This application discloses a kind of warehouse logistics vehicle dispatching method and system, described method, by obtaining task dispensing IP address information, end address information, recalls the path coordinate information of cartographic information module；Then it is calculated the optimum Distribution path information of origin-to-destination from dispensing task by self-adaptive genetic operator；Finally described optimum Distribution path information is sent to terminal node through Zigbee tuning controller, the vehicle carrying described terminal node carries out dispensing task according to optimum Distribution path, therefore save the goods delivery time, thus improve the dispensing efficiency of warehouse logistics.

Description

A warehouse logistics vehicle scheduling method and system

technical field

The invention relates to the field of warehousing and logistics, and more specifically, to a method and system for scheduling warehousing and logistics vehicles.

Background technique

With the advancement of Internet technology, the logistics industry has developed rapidly. Warehousing logistics mainly includes cargo handling, distribution, storage, management, etc. It is an important part of warehousing logistics that the goods can be quickly and accurately delivered to the storage point or the corresponding warehouse. The warehousing logistics distribution mainly involves vehicle scheduling, and there are many factors that affect the efficiency of vehicle distribution, such as distribution routes, warehouse traffic flow, and distribution vehicles.

At present, in the distribution process of warehousing logistics, the distribution route is usually selected artificially, and the distribution efficiency of the artificially selected route is not high.

Therefore, how to improve the efficiency of goods distribution is a technical problem that needs to be solved in warehousing logistics.

Contents of the invention

In order to solve the above technical problems, the present invention provides a warehousing logistics vehicle scheduling method and system, which can obtain the optimal delivery route of the delivery task through the adaptive ant colony algorithm, which can save the delivery time of goods, thereby improving the delivery efficiency of warehousing logistics.

To achieve the above object, the present invention provides the following technical solutions:

The invention discloses a storage logistics vehicle scheduling method, comprising:

Obtaining task delivery information, wherein the task delivery information is task delivery starting point address information and end point address information;

Call the road coordinate information of the map information module;

Based on the task delivery information and road coordinate information, the optimal delivery path information is obtained through adaptive ant colony algorithm calculation;

The optimal delivery route information is sent to the terminal nodes through the Zigbee coordination controller, so that the vehicles carrying the terminal nodes can carry out delivery tasks according to the optimal delivery route.

Preferably, after sending the optimal delivery route information to the terminal node through the Zigbee coordination controller, it also includes:

receiving first feedback information sent by the first terminal node based on a time window mechanism, wherein the first feedback information includes road congestion information and location information of the first terminal node;

Call the road coordinate information of the map information module;

Based on the position information of the first terminal node, the destination address information of the task delivery information and the road coordinate information, the first optimal delivery route information is recalculated through the adaptive ant colony algorithm, wherein the position information of the first terminal node is used as New origin address information;

The first optimal delivery route information is sent to the first terminal node via the Zigbee coordination controller, so that the vehicles carrying the first terminal node avoid congestion and carry out delivery tasks according to the first optimal delivery route information again .

Preferably, after sending the optimal delivery route information to the terminal node through the Zigbee coordination controller, it also includes:

receiving second feedback information sent by a second terminal node based on a time window mechanism, wherein the second feedback information is vehicle fault information and location information of the second terminal node;

Call the road coordinate information of the map information module;

Based on the position information of the second terminal node, the starting position information of the task delivery information and the road coordinate information, the second optimal delivery route information is recalculated through the adaptive ant colony algorithm, wherein the position of the second terminal node The information is the new destination address information;

The Zigbee coordinating controller sends the second optimal delivery route information to the third terminal node, so that the vehicle carrying the third terminal node replaces the vehicle carrying the second terminal node to perform the delivery task.

Preferably, after sending the optimal delivery route information to the terminal node through the Zigbee coordination controller, it also includes:

Obtain the destination address information of the delivery task change;

receiving third feedback information sent by the terminal node based on a time window mechanism, where the third feedback information includes location information of the terminal node;

Call the road coordinate information of the map information module;

Based on the location information of the terminal node, the changed destination address information and road coordinate information, the third optimal delivery route information is recalculated through an adaptive ant colony algorithm, wherein the location information of the terminal node is used as the new starting point address information;

The third optimal delivery route information is sent to the terminal node via the Zigbee coordination controller, so that the vehicle carrying the terminal node performs a delivery task of changing the destination address according to the third optimal delivery route information.

Preferably, after receiving the feedback information sent by the terminal node based on the time window mechanism, the method further includes:

and display the acquired location information of the terminal node.

The invention discloses a warehousing and logistics vehicle dispatching system, comprising:

dispatch center, Zigbee coordination controller and at least one terminal node;

The dispatching center is used to obtain task delivery information, and call the road coordinate information of the map information module, and then calculate the optimal delivery route information based on the task delivery information and road coordinate information using an adaptive ant colony algorithm, and finally transfer the The optimal delivery path information is sent to the Zigbee coordination controller;

The Zigbee coordinating controller is configured to receive the optimal delivery route information sent by the dispatch center, and forward the optimal delivery route information to terminal nodes;

The terminal node is configured to receive the optimal delivery route information sent by the Zigbee coordination controller, so that the vehicle carrying the terminal node performs the delivery task according to the optimal delivery route.

Preferably, the dispatch center is further configured to receive first feedback information sent by the first terminal node based on a time window mechanism, wherein the first feedback information includes road congestion information and location information of the first terminal node, Calling the road coordinate information of the map information module, and then recalculating the first optimal delivery route information through an adaptive ant colony algorithm based on the position information of the first terminal node, the destination address information of the task delivery information, and the road coordinate information, Wherein, the position information of the first terminal node is used as a new starting point address information, and finally the first optimal delivery route information is sent to the Zigbee coordination controller;

The Zigbee coordinating controller is further configured to forward the first feedback information of the first terminal node to the dispatch center, and receive the first optimal delivery path information, and send the first optimal delivery path information forwarding information to the first terminal node;

The first terminal node is used to receive the first optimal delivery route information sent by the Zigbee coordination controller, so that the vehicle carrying the first terminal node avoids congestion and re-delivers according to the first optimal delivery route. Routing information for delivery tasks.

Preferably, the dispatch center is further configured to receive second feedback information sent by the second terminal node based on a time window mechanism, wherein the second feedback information is vehicle failure information and location information of the second terminal node, and Calling the road coordinate information of the map information module, and then recalculating the second optimal delivery route information through an adaptive ant colony algorithm based on the location information of the second terminal node, the starting location information of the task delivery information, and the road coordinate information, Wherein, the position information of the second terminal node is new destination address information, and finally the second optimal distribution path information is sent to the third terminal node through the Zigbee coordination controller, so as to carry the third terminal node The vehicle of the node replaces the vehicle carrying the second terminal node to carry out the distribution task;

The Zigbee coordination controller is further configured to forward the second feedback information of the second terminal node to the dispatch center, and receive the second optimal delivery path information sent by the dispatch center, and send the Forwarding the second optimal delivery route information to the third terminal node;

The second terminal node is configured to send second feedback information to the dispatch center;

The third terminal node is configured to receive the second optimal delivery route information sent by the Zigbee coordination controller, so that the vehicle carrying the third terminal node can replace the vehicle carrying the second terminal node Carry out delivery tasks.

Preferably, the dispatching center is further configured to acquire the terminal address information of the delivery task change, and receive the third feedback information sent by the terminal node based on the time window mechanism, wherein the third feedback information includes the terminal node location information, call the road coordinate information of the map information module, and then based on the location information of the terminal node, the changed terminal address information and road coordinate information, recalculate the third optimal delivery route information through the adaptive ant colony algorithm, Wherein, the position information of the terminal node is used as a new starting point address information, and finally the third optimal delivery route information is sent to the Zigbee coordination controller;

The Zigbee coordination controller is also configured to send the third feedback information of the terminal node to the dispatch center, and receive the third optimal delivery route information sent by the dispatch center, and send the third The optimal delivery route information is forwarded to the terminal node;

The terminal node is also used to receive the third optimal delivery route information sent by the Zigbee coordination controller, so that the vehicle carrying the terminal node performs the delivery of changing the destination address according to the third optimal delivery route information Task.

Preferably, the dispatch center is further configured to display the received location information of the terminal nodes.

It can be seen from the above technical scheme that the beneficial effects of the present invention are: the present invention calls the road coordinate information of the map information module by obtaining the starting point address information and the end point address information of task distribution; The optimal delivery route information from the starting point to the end point of the task; finally, the optimal delivery route information is sent to the terminal node through the Zigbee coordination controller, and the vehicle carrying the terminal node performs the delivery task according to the optimal delivery route, thus saving The delivery time of goods is shortened, thereby improving the delivery efficiency of warehousing logistics.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only It is an embodiment of the present invention, and those skilled in the art can also obtain other drawings according to the provided drawings without creative work.

Fig. 1 is a flow chart of a method for scheduling warehousing logistics vehicles disclosed in an embodiment of the present invention;

Fig. 2 is a flow chart of a method for scheduling warehousing logistics vehicles disclosed in another embodiment of the present invention;

Fig. 3 is a flow chart of a method for scheduling warehousing logistics vehicles disclosed in another embodiment of the present invention;

Fig. 4 is a flow chart of a method for scheduling warehousing logistics vehicles disclosed in another embodiment of the present invention;

Fig. 5 is a system structure diagram of a warehouse logistics vehicle scheduling disclosed in the embodiment of the present invention.

detailed description

The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

The invention discloses a method for scheduling warehousing and logistics vehicles. Referring to FIG. 1, the method includes:

Step S101, obtaining task delivery information;

Among them, the task delivery information is input by the scheduling staff, mainly including the start address information and the end address information of the task delivery;

Step S102, call the road coordinate information of the map information module;

Wherein, the map information module includes all road coordinate information in the entire logistics warehouse area;

Step S103, based on the task delivery information and road coordinate information, calculate the optimal delivery route information through the adaptive ant colony algorithm;

Among them, the process of calculating the optimal delivery route through the adaptive ant algorithm includes:

First of all, in the vehicle scheduling problem, in order to avoid the local stagnation of the ant colony algorithm, it is necessary to limit the pheromone on each path to [τ _min ,τ _max ],

Before generating the first-generation optimal solution, the following formulas are used to determine τ _min (t) and τ _max (t):

${\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; m</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&rho;</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; \&CenterDot;</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; L</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}^{\mathrm{<span\; class="notranslate">\; g</span>}\mathrm{<span\; class="notranslate">\; b</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; min</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; m</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 20</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

After the pheromone has been updated, τ _max (t) is determined using the following formula:

${\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; m</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&rho;</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; \&CenterDot;</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; L</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}^{\mathrm{<span\; class="notranslate">\; g</span>}\mathrm{<span\; class="notranslate">\; b</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; +</span>\frac{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}}{\mathrm{<span\; class="notranslate">\; L</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}^{\mathrm{<span\; class="notranslate">\; g</span>}\mathrm{<span\; class="notranslate">\; b</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

In formula (3), τ _min (t) represents the minimum pheromone concentration, τ _max (t) represents the maximum pheromone concentration, L(s ^gb ) represents the path length of the global optimal solution, and σ represents the "elite ant "quantity;

Select a few "elite ants" that rank high in the path construction, and use them for pheromone update. The update rules are as follows:

${\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; w</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&rho;</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; o</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; +</span>\underset{\mathrm{<span\; class="notranslate">\; u</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; \&Delta;\&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; u</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; \&sigma;\&Delta;\&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; )</span>$

In formula (4): represents the pheromone concentration, 1-ρ represents the pheromone residual factor, and the value range of ρ is u represents the rank of the ant, Represents the increased concentration of ^pheromone when the path length is Lu, Represents the increased concentration of pheromone when the path length L ^* optimal solution;

In order to expand the update range of pheromones, in the iterative process, the iterative incentives are given when the solution is superior to the previous generation, and the iterative penalty is given when the solution is inferior to the previous generation, so as to speed up its convergence speed; The incentive and punishment measures adopted by the path are determined according to the following formula:

In formula (5), Represents the pheromone concentration, L _new and L _old represent the path length, where the path length is calculated from the road coordinate information between the delivery start point and the delivery end point;

After obtaining the updated pheromone, the calculation of the probability of the vehicle on the kth route from the delivery starting point i to the delivery destination j is determined by the following formula:

${\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}\frac{{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&eta;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}}{\underset{\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; \&Omega;</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&eta;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}}<span\; class="notranslate">\; +</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}\frac{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; /</span><span\; class="notranslate">\; (</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; +</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; )</span>}{\underset{\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; \&Omega;</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; /</span><span\; class="notranslate">\; (</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; +</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ,</span>& \begin{array}{cc}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; f</span>}& \mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; \&Omega;</span>}\end{array}\\ \mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; ,</span>& \mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; e</span>}\end{array}\right.<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 6</span>}<span\; class="notranslate">\; )</span>$

In formula (6): τ _ij represents pheromone concentration, α represents information heuristic factor, η _ij represents heuristic function, Denotes the time constraints of client point j, and Indicates the weight coefficient, and satisfies and t _ij represents the time for the vehicle to reach the delivery destination j from the delivery starting point i, Ω={j|j is the accessible workshop}∪{0}, where 0 represents the distribution center;

Finally, the probability of selecting all paths from the delivery start point to the delivery end point is obtained, and the path with the highest probability is regarded as the optimal delivery path;

Step S104, sending the optimal delivery route information to the terminal node through the Zigbee coordination controller, so that the vehicle carrying the terminal node performs the delivery task according to the optimal delivery route;

Among them, the dispatch center selects the number of vehicles required for this delivery task according to the amount of goods to be delivered, and sends the obtained optimal delivery route information to the Zigbee coordination controller. It should be noted that the terminal nodes in the network need to be allocated in advance The address identifier, the Zigbee coordinating controller sends the optimal delivery route information to the terminal node according to the address identifier, so that the vehicle carrying the terminal node can carry out the delivery task according to the optimal delivery route.

In this embodiment, by obtaining the start point address information and end point address information of the task delivery, the road coordinate information of the map information module is called; then the optimal delivery route information from the start point to the end point of the delivery task is obtained through adaptive ant colony algorithm calculation; finally The optimal distribution route information is sent to the terminal node through the Zigbee coordination controller, and the vehicle carrying the terminal node performs the distribution task according to the optimal distribution route, thus saving the delivery time of goods and improving the distribution efficiency of warehousing logistics .

Preferably, in another embodiment, a method for scheduling warehousing and logistics vehicles is disclosed, see FIG. 2, the method includes:

Step S201, obtaining task delivery information;

Wherein, the task delivery information is the starting point address information and the destination address information of the initial delivery task;

Step S202, call the road coordinate information of the map information module;

Step S203, based on the task delivery information and road coordinate information, calculate the optimal delivery route information through the adaptive ant colony algorithm;

Step S204, sending the optimal delivery route information to the first terminal node via the Zigbee coordination controller;

Step S205, receiving first feedback information sent by the first terminal node based on a time window mechanism, wherein the first feedback information includes road congestion information and location information of the first terminal node;

Wherein, receiving the feedback information of the terminal node based on the time window mechanism means setting a time window for multiple delivery tasks at the same time, and the time window represents a time interval, so that the feedback information corresponding to the delivery task is received within each time window, This avoids the conflict of information transmission between different delivery tasks;

Step S206, call the road coordinate information of the map information module;

Step S207, based on the location information of the first terminal node, the destination address information of the task delivery information and the road coordinate information, recalculate the first optimal delivery route information through the adaptive ant colony algorithm, wherein the first terminal node's The location information is used as the new starting point address information;

Step S208, sending the first optimal delivery route information to the first terminal node via the Zigbee coordination controller, so that the vehicle carrying the first terminal node avoids congestion and re-accords to the first optimal delivery route information Carry out delivery tasks.

It should be noted that this embodiment is mainly aimed at the situation of road congestion during the delivery task. In order to ensure that the goods are delivered to the storage location on time, congestion needs to be avoided. Therefore, when the road ahead is congested, the staff of the vehicle carrying the terminal node sends the road congestion information and the location information of the vehicle to the dispatching center through the terminal node. After receiving the feedback information from the terminal node, the dispatch center recalculates a delivery route with the current vehicle location information as the new starting location. Since the dispatch center will automatically discard the congested route after receiving the road congestion information, the re-obtained delivery route, that is, the first optimal delivery route in this embodiment, is not the same route as the congested route.

In this embodiment, when the delivery route is congested, the terminal node will feed back road congestion information to the dispatching center. At this time, the dispatching center will recalculate the delivery route according to the current location of the terminal node and the task delivery end information, thereby avoiding road congestion. , Reduce logistics delivery time. In addition, the dispatch center receives the feedback information of the terminal nodes based on the time window mechanism, which avoids the conflict of information transmission between distribution tasks, thereby improving the efficiency of logistics distribution.

Preferably, in another embodiment, a method for scheduling warehousing and logistics vehicles is disclosed. Referring to FIG. 3 , the method includes:

Step S301, obtaining task delivery information;

Wherein, the task delivery information is the starting point address information and the destination address information of the initial delivery task;

Step S302, call the road coordinate information of the map information module;

Step S303, based on the task delivery information and road coordinate information, calculate the optimal delivery route information through the adaptive ant colony algorithm;

Step S304, sending the optimal delivery route information to the second terminal node via the Zigbee coordination controller;

Step S305, receiving second feedback information sent by the second terminal node based on the time window mechanism, wherein the second feedback information is vehicle fault information and location information of the second terminal node;

Step S306, calling the road coordinate information of the map information module;

Step S307, based on the location information of the second terminal node, the starting location information of the task delivery information and the road coordinate information, recalculate the second optimal delivery route information through the adaptive ant colony algorithm, wherein the second terminal The location information of the node is the new terminal address information;

Step S308, sending the second optimal delivery route information to the third terminal node via the Zigbee coordination controller, so that the vehicle carrying the third terminal node can replace the vehicle carrying the second terminal node to perform the delivery task.

It should be noted that this embodiment is mainly aimed at the situation that the delivery vehicle breaks down during the delivery task and the vehicle needs to be replaced. First of all, the faulty delivery vehicle needs to feed back vehicle fault information and current vehicle location information to the dispatch center. After receiving the feedback information, the dispatch center needs to calculate an optimal path for the replacement vehicle based on the location information of the faulty vehicle, so that the replacement vehicle is It can reach the position of the faulty vehicle with the optimal path, so as to replace the faulty vehicle for delivery tasks.

In this embodiment, the vehicle carrying the second terminal node fails, and the delivery task is interrupted. The replacement vehicle is requested by feeding back the vehicle failure information to the dispatching center. Recalculate an optimal path to reach the location of the faulty vehicle in the shortest time, thereby ensuring the efficiency of logistics distribution.

Preferably, in another embodiment, a method for scheduling warehousing and logistics vehicles is disclosed, see FIG. 4, the method includes:

Step S401, obtaining task delivery information;

Wherein, the task delivery information is the starting point address information and the destination address information of the initial delivery task;

Step S402, call the road coordinate information of the map information module;

Step S403, based on the task delivery information and road coordinate information, calculate the optimal delivery route information through the adaptive ant colony algorithm;

Step S404, sending the optimal delivery route information to the terminal node via the Zigbee coordination controller;

Step S405, obtaining the destination address information of the delivery task modification;

Step S406, receiving third feedback information sent by the terminal node based on a time window mechanism, wherein the third feedback information includes location information of the terminal node;

Step S407, call the road coordinate information of the map information module;

Step S408, based on the location information of the terminal node, the changed destination address information and road coordinate information, recalculate the third optimal delivery route information through the adaptive ant colony algorithm, wherein the location information of the terminal node is used as the new The address information of the starting point;

Step S409, sending the third optimal delivery route information to the terminal node via the Zigbee coordination controller, so that the vehicle carrying the terminal node can perform the delivery task of changing the destination address according to the third optimal delivery route information.

It should be noted that this embodiment is aimed at the situation where the address of the delivery destination is changed in the delivery task. Due to the requirement of the quantity of delivered goods, the same delivery task may require multiple delivery vehicles, and the number of terminal nodes in this example is greater than or equal to one. After the dispatching center obtains the changed destination address information of the delivery task, it recalculates the delivery route according to the changed destination address information, that is, the third optimal delivery route information, and the corresponding terminal node of this delivery task follows the described third optimal delivery route information. 3. Optimal delivery route information for delivery tasks. In addition, step S405 and step S406 only represent an execution sequence of this embodiment, and the action of S406 may be performed first, and then the action of S405 may be performed; or the action of S406 and the action of S405 may be performed simultaneously.

In this embodiment, after obtaining the destination address information of the delivery task change, the dispatching center recalculates the delivery route through the adaptive ant colony algorithm according to the current location information of the delivery vehicle. Vehicles can carry out distribution tasks with a new optimal path, thereby improving the efficiency of logistics distribution.

Preferably, in another embodiment, after receiving the feedback information sent by the terminal node based on the time window mechanism, it further includes:

and display the acquired location information of the terminal node.

In this embodiment, the dispatch center displays the location information fed back by the terminal nodes, so that dispatchers can check the current location of the vehicle and facilitate the statistics of delivery tasks.

Based on the above method, the present invention discloses a warehousing logistics vehicle dispatching system, referring to Fig. 5, the system includes:

Dispatch center 101, Zigbee coordination controller 102 and at least one terminal node 103;

Wherein, the terminal nodes 103 include a first terminal node 1031, a second terminal node 1032, a third terminal node 1033...the nth terminal node 103n; the dispatching center 101 obtains task distribution information, and calls the road of the map information module Coordinate information, then based on the task delivery information and road coordinate information, adopt the adaptive ant colony algorithm to calculate the optimal delivery route information, and finally send the optimal delivery route information to the Zigbee coordination controller 102;

The Zigbee coordination controller 102 is configured to receive the optimal delivery route information sent by the dispatch center 101, and forward the optimal delivery route information to the terminal node 103;

The terminal node 103 is used to receive the optimal delivery route information sent by the Zigbee coordination controller 102, so that the vehicle carrying the terminal node 103 performs the delivery task according to the optimal delivery route.

Preferably, the dispatch center 101 is also configured to receive feedback information from the terminal node 103 based on a time window mechanism, and the terminal node 103 feeds back real-time delivery information to the dispatch center 101 through the Zigbee coordination controller 102; wherein the feedback information includes The location information of the terminal nodes, road congestion information, vehicle failure information, etc., and according to the feedback information, the dispatch center 101 recalculates the new optimal delivery route through the adaptive ant colony algorithm, so as to ensure that when the delivery vehicles encounter road congestion, Choose the distribution route to avoid congestion, and when the vehicle fails, it can quickly dispatch new distribution vehicles to replace the faulty vehicle, thereby ensuring the efficiency of warehousing logistics distribution. In addition, when the delivery address is changed, the dispatch center 101 can adjust the delivery route in time to ensure that the goods are delivered to the delivery destination in a timely and accurate manner.

In this embodiment, by setting up a Zigbee wireless network, the optimal distribution route calculated by the dispatching center 101 can be efficiently transmitted to the distribution vehicle, wherein the Zigbee wireless network has the advantages of short distance, self-organization, low power consumption, and low data rate. , low complexity, low delay, low cost and other characteristics, it can meet the requirements of information communication within the scope of storage to the greatest extent. The data communication between the dispatch center 101 and the Zigbee coordination controller 102 is carried out through a serial port or a bus. When there are many warehousing logistics distribution tasks and the amount of data to be transmitted is large, the bus connection dispatch center 101 and the Zigbee coordination controller 102 are used. , For example, such as large-scale parts storage and distribution systems, large-scale dock logistics warehouses, etc., there are many kinds of goods in storage, the quantity is large, and more distribution vehicles are required. For large-scale dock logistics warehouses, Zigbee wireless networks need to add multiple routing nodes to realize data transmission.

It should be noted that, in the warehousing logistics vehicle dispatching system disclosed in this embodiment, please refer to the method embodiments corresponding to FIGS. 1 to 4 for the specific working process of each component, which will not be repeated here.

The above description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention will not be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. a warehouse logistics vehicle dispatching method, it is characterised in that including:

Acquisition task distribution information, wherein said task distribution information is task dispensing IP address information, end address information；

The path coordinate information of invocation map information module；

Based on described task distribution information and path coordinate information, it is calculated optimum Distribution path by self-adaptive genetic operator Information；

Described optimum Distribution path information is sent to terminal node through Zigbee tuning controller, in order to carry described terminal The vehicle of node carries out dispensing task according to optimum Distribution path.

Method the most according to claim 1, it is characterised in that described described optimum Distribution path information is assisted through Zigbee After adjusting controller to be sent to terminal node, also include:

The first feedback information that first terminal node sends, wherein, described first feedback information bag is received based on time window mechanism Include road congestion information and the positional information of described first terminal node；

The path coordinate information of invocation map information module；

Positional information based on first terminal node, the end address information of task distribution information and path coordinate information, pass through Self-adaptive genetic operator recalculates the first optimum Distribution path information that obtains, wherein, the position letter of described first terminal node Breath is as new IP address information；

Described first optimum Distribution path information is sent to first terminal node through Zigbee tuning controller, in order to carry The vehicle of described first terminal node is avoided blocking up and is again carried out dispensing task according to the described first optimum Distribution path information.

Method the most according to claim 1, it is characterised in that described described optimum Distribution path information is assisted through Zigbee After adjusting controller to be sent to terminal node, also include:

Receiving, based on time window mechanism, the second feedback information that the second terminal node sends, wherein said second feedback information is car Fault message and the positional information of described second terminal node；

The path coordinate information of invocation map information module；

Positional information based on described second terminal node, the start position information of task distribution information and path coordinate information, Recalculated by self-adaptive genetic operator and obtain the second optimum Distribution path information, wherein, the position of described second terminal node Confidence breath is new end address information；

The described second optimum Distribution path information is sent to third terminal node, in order to carry through Zigbee tuning controller State the vehicle of third terminal node to replace and carry the vehicle of described second terminal node and carry out dispensing task.

Method the most according to claim 1, it is characterised in that described described optimum Distribution path information is assisted through Zigbee After adjusting controller to be sent to terminal node, also include:

Obtain the end address information of dispensing task change；

The 3rd feedback information that described terminal node sends, wherein, described 3rd feedback information bag is received based on time window mechanism Include the positional information of described terminal node；

The path coordinate information of invocation map information module；

Positional information based on terminal node, the end address information of change and path coordinate information, calculated by self-adapting ant colony Method recalculates the 3rd optimum Distribution path information that obtains, and wherein, the positional information of described terminal node is as new starting point ground Location information；

Described 3rd optimum Distribution path information is sent to described terminal node through Zigbee tuning controller, in order to carry The vehicle of described terminal node is changed the dispensing task of end address according to the described 3rd optimum Distribution path information.

5. according to the method described in claim 2～4 any one, it is characterised in that described based on time window mechanism receive institute After stating the feedback information that terminal node sends, also include:

The positional information of the described terminal node obtained is shown.

6. a warehouse logistics vehicle dispatch system, it is characterised in that including:

Control centre, Zigbee tuning controller and at least one terminal node；

Described control centre, is used for obtaining task distribution information, and the path coordinate information of invocation map information module, then base Self-adaptive genetic operator is used to be calculated optimum Distribution path information in described task distribution information and path coordinate information, After described optimum Distribution path information is sent to described Zigbee tuning controller；

Described Zigbee tuning controller, for receiving the optimum Distribution path information that described control centre sends, and by described Optimum Distribution path information is transmitted to terminal node；

Described terminal node, for receiving the described optimum Distribution path information that described Zigbee tuning controller sends, in order to The vehicle carrying described terminal node carries out dispensing task according to optimum Distribution path.

System the most according to claim 6, it is characterised in that

Described control centre, be additionally operable to based on time window mechanism receive first terminal node send the first feedback information, wherein, Described first feedback information includes road congestion information and the positional information of described first terminal node, invocation map information module Path coordinate information, be then based on the end address information of the positional information of described first terminal node, task distribution information With path coordinate information, recalculated the first optimum Distribution path information that obtains by self-adaptive genetic operator, wherein, described the Described first optimum Distribution path information, as new IP address information, is finally sent to by the positional information of one terminal node Described Zigbee tuning controller；

Described Zigbee tuning controller, is additionally operable to forward the first feedback letter of described first terminal node to described control centre Breath, and receive described first optimum Distribution path information, and the described first optimum Distribution path information is transmitted to described the One terminal node；

Described first terminal node, for receiving the described first optimum Distribution path letter that described Zigbee tuning controller sends Breath, in order to carry described first terminal node vehicle and avoid blocking up and again carry out according to described first optimum Distribution path information Dispensing task.

System the most according to claim 6, it is characterised in that

Described control centre, is additionally operable to receive the second feedback information that the second terminal node sends, wherein based on time window mechanism Described second feedback information is vehicle trouble messages and the positional information of described second terminal node, and invocation map information mould The path coordinate information of block, is then based on the start position letter of the positional information of described second terminal node, task distribution information Breath and path coordinate information, recalculate the second optimum Distribution path information that obtains by self-adaptive genetic operator, wherein, described The positional information of the second terminal node is new end address information, after through described Zigbee tuning controller to third terminal Node sends the described second optimum Distribution path information, in order to the vehicle replacement carrying described third terminal node is carried The vehicle stating the second terminal node carries out dispensing task；

Described Zigbee tuning controller, is additionally operable to forward the second feedback letter of described second terminal node to described control centre Breath, and receive the described second optimum Distribution path information that described control centre sends, and by the described second optimum dispensing road Footpath information is transmitted to described third terminal node；

Described second terminal node, for sending the second feedback information to described control centre；

Described third terminal node, for receiving the described second optimum Distribution path letter that described Zigbee tuning controller sends Breath, in order to carry the vehicle of described third terminal node and replace and carry the vehicle of described second terminal node and carry out dispensing and appoint Business.

System the most according to claim 6, it is characterised in that

Described control centre, is additionally operable to obtain the end address information of dispensing task change, and receives based on time window mechanism The 3rd feedback information that described terminal node sends, wherein, described 3rd feedback information includes the position letter of described terminal node Breath, the path coordinate information of invocation map information module, it is then based on the terminal ground of the positional information of described terminal node, change Location information and path coordinate information, recalculate the 3rd optimum Distribution path information that obtains by self-adaptive genetic operator, wherein, Described 3rd optimum Distribution path information, as new IP address information, is finally sent by the positional information of described terminal node To described Zigbee tuning controller；

Described Zigbee tuning controller, is additionally operable to send the 3rd feedback information of described terminal node to described control centre, And receive the described 3rd optimum Distribution path information that described control centre sends, and by the described 3rd optimum Distribution path letter Breath is transmitted to described terminal node；

Described terminal node, is additionally operable to receive the 3rd optimum Distribution path information that described Zigbee tuning controller sends, with Portable belt has the vehicle of described terminal node to be changed the dispensing of end address according to the described 3rd optimum Distribution path information Task.

10. according to the system described in claim 7～9 any one, it is characterised in that

Described control centre, is additionally operable to show the positional information of the terminal node received.