CN111754147A - Road division method, system, device and computer-readable storage medium - Google Patents

Abstract

The embodiment of the invention provides a road division method, a road division system, a road division device and a computer readable storage medium. The road division method comprises the following steps: dividing a distribution area into a plurality of distribution units; establishing an association relation between the order address and the delivery unit; respectively corresponding a plurality of pieces of order distribution data contained in the first order distribution data set to the plurality of distribution units based on the incidence relation; acquiring statistical information of order distribution data of each distribution unit; and combining the distribution units to obtain a plurality of road areas based on the statistical information. The road area division method for obtaining the road areas through the combined distribution units is not only beneficial to quickly adjusting the road areas, but also beneficial to the distribution personnel to keep the working efficiency because most distribution units contained in one road area are not changed and have little influence on the daily work of the distribution personnel.

Description

Road division method, system, device and computer-readable storage medium

technical field

The present invention relates to the field of logistics, in particular to a method, system, device and computer-readable storage medium for dividing a road area.

Background technique

The planning of the existing distribution range is mainly based on business needs, and the site management personnel divide the road area of the delivery staff based on past experience, such as the order volume and timeliness requirements of a certain area (such as the unit requirements must be delivered during the day, etc.) to carry out tasks such as distribute.

However, due to various reasons such as business growth, personnel changes, and site distribution changes, the road areas of the couriers frequently change, and the site invests a lot of manpower and material resources in the maintenance of road areas to meet business needs. With the increase of logistics scale, manual maintenance of road areas has gradually made it impossible to quickly respond to site needs. In some cases, the untimely update of road areas has led to the dispatch errors of the pre-sorting system.

SUMMARY OF THE INVENTION

In view of this, the embodiments of the present invention provide a road area division method to solve the problems existing in the existing road area division process.

In a first aspect, an embodiment of the present invention provides a method for dividing a road area, including:

Divide the delivery area into multiple delivery units;

Establish an association between the order address and the delivery unit;

Based on the association relationship, the multiple order delivery data included in the first order delivery data set are respectively corresponding to the multiple delivery units;

Get statistics on order fulfillment data for each fulfillment unit; and

Based on the statistical information, the plurality of delivery units are combined to obtain a plurality of road areas.

Optionally, it also includes: verifying the order address of the order delivery data included in the second order delivery data set based on the proper investment GIS data, and using the order delivery data that has passed the verification as an order in the first order delivery data set. Shipping data.

Optionally, if the offset between the GIS data corresponding to the order address of the order delivery data contained in the second order delivery data set and the properly delivered GIS data is less than the first set threshold, it is considered that the first 2. The order address of the order delivery data in the order delivery data set is accurate.

Optionally, also include:

Use GIS technology to perform positive analysis on the order address of the order delivery data included in the second order delivery data set to obtain a positive analysis result, and use GIS technology to perform reverse analysis on the positive analysis result to obtain a reverse analysis address;

Verifying the order address of the second order delivery data set using the reverse parsed address; and

If the similarity between the order address of the order delivery data of the second order delivery data set and the reverse resolution address exceeds a second set threshold, the order delivery data whose similarity exceeds the second set threshold is used as the first The order fulfillment data in the order fulfillment dataset.

Optionally, the method further includes: performing natural language processing on the reverse parsed address and the order address of the order delivery data in the second order delivery data set.

Optionally, it also includes: the first verification result of the order address verification of the order delivery data of the second order delivery data set according to the properly cast GIS data and the verification of the second order delivery data set by GIS technology. For the second verification result of the order address verification of the order delivery data, the first order delivery dataset is obtained from the second order delivery dataset.

Optionally, the method further includes: obtaining the proper delivery GIS data from the GIS trajectory data of the delivery personnel.

Optionally, the method further includes: establishing a correspondence between the multiple road areas and multiple delivery personnel.

Optionally, the dividing the delivery area into multiple delivery units includes:

converting the order address of the order delivery data contained in the third order delivery data set into corresponding GIS data; and

Using a clustering algorithm, the distribution area is divided into a plurality of distribution units according to the corresponding GIS data.

Optionally, the clustering algorithm is a k-means algorithm.

Optionally, the time period of the order delivery data included in the third order delivery dataset is smaller than the time period of the order delivery data included in the first order delivery dataset.

Optionally, the method further includes: performing desensitization processing on the order delivery data in the first order delivery data set.

Optionally, the statistical information is the daily average order quantity of each delivery unit, and the combination of the multiple delivery units to obtain multiple road areas based on the statistical information includes:

According to the preset number of road areas and the daily average order quantity of each delivery unit, adjacent delivery units are combined together to form the plurality of road areas.

Optionally, the method further includes: providing a visual interface, where the plurality of road areas are divided by dragging and dropping the plurality of delivery units.

According to a second aspect of the embodiments of the present invention, a system for dividing a road area is provided, including:

The distribution unit division module divides the distribution area into multiple distribution units;

The address association module establishes an association relationship between the order address and the delivery unit;

a delivery data correspondence module, configured to respectively correspond to the multiple delivery units of the multiple order delivery data included in the first order delivery data set based on the association relationship;

A delivery data statistics module for obtaining the statistics of order delivery data of each delivery unit; and

A delivery unit combination module, configured to combine the multiple delivery units to obtain multiple road areas based on the statistical information.

Optionally, it also includes: a first verification module, configured to verify the order address of the order delivery data contained in the second order delivery data set based on the GIS data of the proper investment, and use the verified order delivery data as the described order delivery data. Order delivery data in the first order delivery dataset.

Optionally, it also includes: a second verification module, configured to use GIS technology to positively analyze the order address of the order distribution data included in the second order distribution data set, obtain a positive analysis result, and use GIS technology to analyze the order address of the order distribution data set. Perform reverse parsing on the positive parsing result to obtain a reverse parsing address; use the reverse parsing address to verify the order address of the second order delivery data set; and if the order delivery data of the second order delivery dataset The similarity between the address and the reverse parsed address exceeds the second set threshold, and the order delivery data whose similarity exceeds the second set threshold is regarded as the order delivery data in the first order delivery data set.

Optionally, the method further includes: a natural language processing module, configured to perform natural language processing on the reverse parsed address and the order address of the order delivery data of the second order delivery data set.

Optionally, the distribution unit division module includes:

converting the order address of the order delivery data contained in the third order delivery data set into corresponding GIS data; and

Using a clustering algorithm, the distribution area is divided into a plurality of distribution units according to the corresponding GIS data.

Optionally, the time period of the order delivery data included in the third order delivery dataset is smaller than the time period of the order delivery data included in the first order delivery dataset.

Optionally, the statistical information is the daily average order quantity of each distribution unit, and the distribution unit combination module includes:

According to the preset number of road areas and the daily average order quantity of each delivery unit, adjacent delivery units are combined together to form the plurality of road areas.

Clustering Algorithm Corresponds to Clustering Algorithm In the third aspect, an embodiment of the present invention provides a computer-readable storage medium, where computer instructions are stored in the computer-readable storage medium, and when the computer instructions are executed, any one of the above-mentioned instructions is implemented. method of road division.

In a fourth aspect, an embodiment of the present invention provides an apparatus for dividing a road area, including:

memory for storing computer instructions;

A processor, coupled to the memory, configured to execute the method for implementing any one of the above-mentioned ways based on computer instructions stored in the memory.

The embodiments of the present invention have the following advantages or beneficial effects: the road area division method for obtaining road areas by combining distribution units not only helps to quickly adjust road areas, but also, since most of the distribution units included in a road area have not changed, for distribution The day-to-day work of the personnel has little impact, so it also helps the delivery personnel to maintain their productivity.

Description of drawings

The above and other objects, features and advantages of the present invention will become more apparent from the description of embodiments of the present invention with reference to the following drawings, in which:

FIG. 1 is a flowchart of a method for dividing a road area according to a first embodiment of the present invention;

Fig. 2 is to show distribution area, distribution unit and road area on the geographic information system;

FIG. 3 is an exemplary flowchart of step S101 in the first embodiment of the present invention;

FIG. 4 is a flowchart of a method for dividing a road area according to a second embodiment of the present invention;

FIG. 5 is a flowchart of a road area division method according to a third embodiment of the present invention;

FIG. 6 is used to further illustrate steps S503-S505 of the third embodiment of the present invention;

7 is a structural diagram of a system for dividing a road area according to a fourth embodiment of the present invention;

FIG. 8 is a structural diagram of a road area dividing apparatus according to a sixth embodiment of the present invention.

Detailed ways

The present invention is described below based on examples, but the present invention is not limited to these examples only. In the following detailed description of the invention, some specific details are described in detail. The present invention can be fully understood by those skilled in the art without the description of these detailed parts. In order to avoid obscuring the essence of the present invention, well-known methods, procedures and processes are not described in detail. Additionally, the drawings are not necessarily to scale.

Referring to FIG. 1, FIG. 1 shows a flowchart of a method for dividing a road area according to a first embodiment of the present invention. In this embodiment, the delivery area is first divided into delivery units, and then the road areas are divided based on the delivery units. Figure 2 shows delivery areas, delivery units and road zones on a geographic information system. Referring to FIG. 2 , the delivery area 10 is, for example, a delivery range corresponding to a delivery station, and has a corresponding boundary on the geographic information system. The delivery area 10 is divided into a number of delivery units such as 1001-1007. Adjacent distribution units are grouped together to form road zones. In the figure, the road area and delivery area are marked with solid lines, and the delivery units are marked with dotted lines. As can be seen from the figure, the road area 100 is composed of delivery units 1001-1007. The respective areas of the dispensing units 1001-1007 are not the same. The following is a detailed description of the embodiment of FIG. 1 .

In step S101, the delivery area is divided into a plurality of delivery units.

As shown in FIG. 2 , the delivery area can be divided into multiple delivery units based on the geographic information system. For example, count all the valid delivery addresses in the delivery area for historical order delivery data, and divide the delivery area into multiple delivery units according to the valid delivery addresses, so that the valid delivery addresses on each delivery unit are roughly equal, or the effective delivery addresses with strong correlation Delivery addresses are assigned within the same shipping unit. Here, the effective delivery address with strong correlation is the effective delivery address within the set threshold from the set center point. It should be pointed out that the respective areas of the multiple distribution units obtained by dividing the distribution units may be different.

In step S102, an association relationship is established between the order address and the delivery unit.

The order address can come from the order data. When the order data is generated, the order address is stored in the order address data set at the same time. Then, the order address is converted into GIS data (including latitude and longitude information), and the relationship between the order address and the delivery unit is determined according to the latitude and longitude information of the order address and the GIS fence information of each delivery unit.

In step S103, based on the association relationship, multiple pieces of order delivery data included in the first order delivery data set are respectively corresponding to multiple delivery units.

According to the relationship between the order address and the delivery unit, the relationship between the order delivery data included in the first order delivery data set and the delivery unit is realized.

In step S104, the statistical information of the order delivery data of each delivery unit is acquired.

In step S105, based on the statistical information, multiple delivery units are combined to obtain multiple delivery road areas.

Since the order delivery data included in the first order delivery data set has been mapped to multiple delivery units one by one in step S103, in step S104, the number of order delivery data on each delivery unit can be counted, and then In step S105, the multiple delivery units are divided into multiple road areas according to the statistical information of the order delivery data on each delivery unit. Usually, the average daily order quantity per distribution unit is used as an indicator to measure the capacity of the distribution unit. The average daily order quantity can be calculated based on the current 30-day or 60-day historical order delivery data. Using the daily average order quantity can smooth the fluctuation of real-time order delivery data. Of course, the present invention is not limited to this. After the road area division is completed, a corresponding relationship is established between the road area and the delivery personnel. In practical activities, arrange the road areas that the delivery personnel are responsible for as needed.

The embodiments of the present invention are applicable to various scenarios of dividing road areas. For example, when the traffic volume increases, since the newly added traffic volume is not evenly distributed in the currently existing multiple road areas, it is necessary to adjust the currently existing multiple road areas. Since the delivery unit remains unchanged, the statistical information of the order delivery data on the currently existing delivery unit is recalculated, and the delivery unit included in each road area is adjusted accordingly.

The road area division method for obtaining road areas by combining distribution units in this embodiment not only helps to quickly adjust road areas, but also has little impact on the daily work of distribution personnel because most of the distribution units included in a road area have not changed. , thus also helping the delivery staff maintain their productivity.

It should be pointed out that a large amount of sensitive data is retained in the original order delivery data of the e-commerce system, such as user name, user detailed address, mobile phone number, etc. These information are not necessary in the present invention, so these original orders can be The distribution data is desensitized to hide or filter out the above-mentioned sensitive information. The desensitized order delivery data generally includes the following fields: order number, order address, and delivery time.

FIG. 3 is an exemplary flowchart of step S101 in the first embodiment of the present invention. This embodiment describes how to divide a delivery area into multiple delivery units. Specifically include the following steps.

In step S1011, a third order delivery data set of the delivery area is acquired.

In step S1012, the order address of the order delivery data in the third order delivery data set is converted into corresponding GIS data.

In step S1013, the delivery area is divided into a plurality of delivery units according to the GIS data corresponding to the order address of the order delivery data of the third order delivery data set.

The third order delivery data set in this embodiment generally selects short-term historical order delivery data, such as one-year historical order delivery data, while the first order delivery data set in step S102 generally selects long-term historical order delivery data, such as all historical orders data. The first order delivery data set and the third order delivery data set are preferably desensitized and/or preprocessed historical order delivery data. Preprocessing includes, for example, cleaning out the delivery data of some orders that have been cancelled, supplementing the missing information in the order address, and so on. Supplement the missing information in the order address. For example, if the order address in the order delivery data is not a complete zip code address, the complete zip code address includes information such as province, city, district, community name, building number, etc. The information of the corresponding level of the order address is fully supplemented.

In this embodiment, the distribution area can be divided into multiple distribution units according to the GIS data in the following manner: the GIS data is marked on the geographic information system, and a clustering algorithm is used to classify the GIS data that are relatively close to each other on the geographic information system. for a delivery unit. The clustering algorithm does not need to set the number of distribution units, and can only determine the number of distribution units according to the actual physical state.

In some embodiments, the clustering algorithm method is a k-means algorithm. The K-means algorithm is a typical distance-based clustering algorithm, which uses distance as an evaluation index for similarity, that is, it is considered that the closer the distance between two objects, the greater the similarity.

FIG. 4 is a flowchart of a method for dividing a road area according to a second embodiment of the present invention.

In step S401, the delivery area is divided into a plurality of delivery units.

In step S402, an association relationship is established between the order address and the delivery unit.

In step S403, the order address of the order delivery data included in the second order delivery data set is verified based on the proper delivery GIS data to obtain the first order delivery data set.

In step S404, based on the association relationship, multiple pieces of order delivery data included in the first order delivery data set are respectively corresponding to multiple delivery units.

In step S405, the statistical information of the first order delivery data set on the multiple delivery units is acquired.

In step S406, based on the statistical information, multiple delivery routes are obtained by combining multiple delivery units.

Wherein, steps S401-S402, S404-S406 are the same as steps S101-S105 in FIG. 1, and details are not repeated here.

In step S403, the proper delivery GIS data is the GIS data when the delivery personnel deliver the package, generally including longitude and latitude information and proper delivery time. The proper GIS data can come from the delivery personnel. When the delivery personnel deliver the package, the current latitude and longitude information and time will be uploaded through the terminal carried by the delivery personnel as the proper GIS data. Duotou GIS data can also come from delivery robots or drones. When the drone or delivery robot delivers the package, upload the current latitude and longitude information and time as Duotou GIS data.

In step S402, the order address in the second order delivery data set is checked based on the proper delivery GIS data to determine whether the order address resolution GIS is correct, and the second order delivery data set that resolves the correct order address is classified as the first order Shipping dataset. Specifically, calculate the offset between the latitude and longitude when the delivery is due and the latitude and longitude converted from the order address, and judge whether the order address is accurate according to the offset. If the offset exceeds a set threshold, the order geocoding GIS is considered likely to be inaccurate. In one example, the offset is calculated using the following formula:

Among them, lat1, lng1 represent the latitude and longitude of point A, lat2, lng2 represent the latitude and longitude of point B, and 6378.137 is the radius of the earth in kilometers. A is the delivery location, and point B is the order address. In this embodiment, the ratio of the offset and the delivery distance may also be used to determine whether the second order delivery data set is accurate. Similarly, if the ratio exceeds a set threshold, the order address is considered inaccurate.

FIG. 5 is a flowchart of a road area division method according to a third embodiment of the present invention. Specifically include the following steps.

In step S501, the delivery area is divided into a plurality of delivery units.

In step S502, an association relationship is established between the order address and the delivery unit

In step S503 , the order address of the order delivery data included in the second order delivery data set is verified based on the proper delivery GIS data, and a first verification result is obtained.

In step S504, GIS technology is used to perform positive analysis on the order address of the order delivery data included in the second order delivery data set, and a positive analysis result is obtained. The second verification result is obtained from the order address and the reverse-parsed address in the delivery data.

In step S505, the first order delivery data set is obtained from the second order delivery data set according to the first verification result and the second verification result.

In step S506, based on the association relationship, multiple pieces of order delivery data included in the first order delivery data set are respectively corresponding to multiple delivery units.

In step S507, the statistical information of the first order delivery data set on the multiple delivery units is acquired.

In step S508, based on the statistical information, a plurality of delivery units are combined to obtain a plurality of delivery road areas.

Steps S501-S502 are the same as steps S101-S102 in FIG. 1 , and steps S506-S508 are the same as steps S103-S105 in FIG. 1 , and will not be repeated here. In steps S503-S505, the verification result is obtained by combining the two verification methods, and the first order delivery data set is obtained from the second order delivery data set according to the verification result.

In step S503, the order address in the second order delivery data set is verified based on the duly voted GIS data, and a first verification result is obtained. Proper delivery GIS data is the GIS data when the delivery personnel deliver the package, generally including latitude and longitude information and delivery time. The proper investment GIS data can come from the delivery personnel. The terminal carried by the delivery personnel regularly uploads the GIS trajectory data, and obtains the proper investment GIS data from the GIS trajectory data.

In step S504, the order address of the order delivery data included in the second order delivery data set is positively analyzed by using GIS technology, and a positive analysis result is obtained. Second, the order address and the reverse analysis address of the order delivery data included in the order delivery data set are obtained, and a second verification result is obtained. Here, positive parsing is to obtain the latitude and longitude information based on the order address, and reverse parsing is to obtain the order address based on the latitude and longitude information. In step S504, whether the order address is accurate is determined through reverse parsing after forward parsing. In some embodiments, if the similarity between the reverse parsed address and the order address is greater than a set threshold, the order address may be considered accurate. The reverse parsing address and the order address are generally matched by natural language processing (NLP). For example, Beijing Anzhenxili and Beijing Anzhenxili, the similarity obtained by natural language processing is relatively high.

In step S505, the first order delivery data set is obtained from the second order delivery data set by synthesizing the first verification result and the second verification result.

Based on steps S503 and S504, two verification results are obtained for the order address, and the first order delivery dataset is obtained from the second order delivery dataset according to the two verification results. For example, if the first verification result is that the order address is accurate, and the second verification result is that the order address is accurate, the corresponding second order delivery data set may be used as the first order delivery data set. For another example, if the first verification result is that the order address is accurate, and the second verification result is that the order address is inaccurate, manual intervention is performed to judge and correct to obtain the first order delivery data set.

To sum up, the embodiment of the present invention not only uses the proper investment GIS data to verify the order address, but also transforms the order address through forward and reverse analysis of GIS technology, and verifies the order address according to the reverse analysis address, and according to the two verification results. Obtain the first order delivery data set, ensure that the order address is accurate through double verification, and then divide the road areas according to the statistical information of the first order delivery data set, so as to ensure the accuracy of the road area division, and then ensure the divided road areas. should be roughly equivalent.

FIG. 6 shows steps S503-S505 for further explaining the third embodiment of the present invention. In this embodiment, the A check and the B check are performed simultaneously, and the results of the A check and the B check are combined twice to determine the final check result. First, obtain the delivery time 402 and the track 401 of the delivery staff, clean the track 401 of delivery staff (ie 403), and obtain the GIS data 404 for delivery. The GIS data for delivery includes the latitude and longitude information and the delivery time. The order address 400 in the delivery data set is converted to obtain the corresponding GIS data 405, and the verification A verifies that the GIS data 404 and the GIS data 405 are properly delivered. 406, if the two are not close, for example, greater than a set threshold, the order address is considered to be inaccurate, that is, 407. At the same time, the order address 408 is positively parsed (ie 501) to obtain the GIS data 409, the GIS data 409 is reversely parsed (ie 502), the reverse parsed address 410 is obtained, and the order address 408 and the reverse parsed address 410 are subjected to natural language processing NLP (ie 411), and verify it through verification B. If the similarity between the two exceeds 80%, the order address is considered accurate (ie 412), otherwise the order address is considered inaccurate (ie 413). Comprehensive verification A and Verify the verification result of B, and obtain four kinds of results: 1) The judgment of A is accurate and the judgment of B is accurate, that is, 414 in the figure, it is generally considered that the order address is accurate, and the second order delivery data set can be used as the first embodiment. 2) The judgment of A is accurate and the judgment of B is inaccurate, that is, 415 in the figure, then it is generally considered that the address has a high degree of accuracy, and the address contains an alias, that is, 419 in the figure, and the order delivery data has been manually processed by 422 After the correction, it is used as the first order delivery data set; 3) The judgment of A is inaccurate and the judgment of B is accurate, i.e. 416 in the figure, then it is considered that the address is more accurate and the correct delivery address may be wrong, i.e. 420 in the figure, the order delivery data has been manually processed After correction, 422, it is used as the first order delivery data set; 4) A judgment is inaccurate and B judgment is inaccurate, ie 417 in the figure, the order delivery data is not classified as the first order delivery data set.

Optionally, this embodiment may further provide a visual interface, and the road areas are divided based on the visual interface. A visual interface is shown in Figure 2. Based on the geographic information system, the divided distribution units are marked on the geographic information system, and the statistical information of the distribution unit is marked on each distribution unit. The delivery units are combined together to get the road area. On another visual interface, the delivery unit is similar to one module, and the road area is combined by dragging and dropping the delivery unit. Of course, there are other restrictions in the combining process, for example, only adjacent distribution units can be combined together. This visual interface has strong application scenarios and greatly facilitates managers. Managers can continuously combine and separate distribution units on the visual interface to obtain the optimal road division scheme.

FIG. 7 is a structural diagram of a road division system according to a fourth embodiment of the present invention. The road area division system 700 includes: a distribution unit division module 701 , an address association module 702 , a distribution data correspondence module 703 , a distribution data statistics module 704 and a distribution unit combination module 705 .

The delivery unit division module 701 is used to divide the delivery area into a plurality of delivery units. The address association module 702 is used to establish an association relationship between the order address and the delivery unit. The delivery data correspondence module 703 is configured to, based on the association relationship, respectively correspond to the multiple delivery units of the multiple order delivery data included in the first order delivery data set. The delivery data statistics module 703 is used to obtain the statistical information of the order delivery data of each delivery unit. The delivery unit combining module 704 is configured to combine the multiple delivery units to obtain multiple road areas based on the statistical information.

In this road area division system, the delivery area is divided into multiple delivery units, and an association relationship is established between the delivery unit and the order address, so as to associate the order delivery data with the delivery unit, and then count the associations on each delivery unit. The number of order delivery data, and based on statistical values, multiple delivery units are divided into multiple road areas. In this system, the road area division method obtained by combining distribution units not only helps to quickly adjust the road area, but also, since most of the distribution units contained in a road area have not changed, it will not affect the daily work of the distribution personnel. Larger, so it also helps the delivery staff maintain their productivity.

In some embodiments, the above-mentioned road area division system further includes a first verification module, configured to verify the order address of the order delivery data included in the second order delivery data set based on the GIS data of proper investment, and verify the order address of the order delivery data included in the second order delivery data set. The order delivery data is used as the order delivery data in the first order delivery data set.

In some embodiments, the above-mentioned road area division system further includes a second verification module for performing positive analysis on the order address of the order delivery data included in the second order delivery data set by using GIS technology, to obtain a positive analysis result, and using GIS technology Perform reverse parsing on the positive parsing result to obtain the reverse parsing address; use the reverse parsing address to verify the order address of the second order delivery data set; and if the order address and reverse parsing address of the order delivery data of the second order delivery dataset If the similarity exceeds the second set threshold, the order delivery data whose similarity exceeds the second set threshold is regarded as the order delivery data in the first order delivery data set.

In some embodiments, the above-mentioned road area division system includes a combination of the above-mentioned first verification module and first verification module, that is, the first verification result and the second verification result are obtained from the second order delivery data set. 1. Order delivery data.

In some embodiments, the delivery unit division module is configured to convert the order address of the order delivery data included in the third order delivery data set into corresponding GIS data, and then use a clustering algorithm to divide the delivery area into the corresponding GIS data according to the corresponding GIS data. Multiple delivery units. It should be noted that the time period of the order delivery data of the third order delivery data set for dividing the delivery unit is generally smaller than the time period of the order delivery data contained in the first order delivery data set for dividing the road area. For example, the third order delivery data set is historical order delivery data of the current year, and the first order delivery data set and the second order delivery data set use all historical order delivery data. The shipping units determined by the third order shipping dataset generally remain unchanged. Since the address information on the delivery unit generally does not change easily, the delivery unit does not need to be modified frequently. What needs to be clarified here is that the change of the building where the address is located does not mean that the address information has changed. For example, a bungalow becomes a tall building, but the corresponding address information remains the same, but the description may be different.

In some embodiments, the statistical information in the order delivery data statistics module 703 is the daily average order quantity of each delivery unit, and the delivery unit combination module 704 includes: according to the preset number of road areas and the daily average order quantity of each delivery unit Quantity, grouping adjacent distribution units together to form multiple road zones.

In some embodiments, the road area dividing system further includes: a visualization module, configured to provide a visual interface, on which a plurality of road areas are divided by dragging and dropping a plurality of delivery units.

It should be understood that the first order delivery data set, the second order delivery data set and the third order delivery data set herein are only used to distinguish different order delivery data, and do not represent priority or level distinction.

FIG. 8 is a structural diagram of a road area dividing apparatus according to a sixth embodiment of the present invention. The device shown in FIG. 8 is only an example, and should not constitute any limitation on the function and scope of use of the embodiments of the present invention.

Referring to FIG. 8 , the apparatus includes a processor 801 , a memory 802 and an input and output device 803 connected by a bus. The memory 802 includes read-only memory (ROM) and random access memory (RAM). Various computer instructions and data required to perform system functions are stored in the memory 802. The processor 801 reads various computer instructions from the memory 802 to execute. Various appropriate actions and handling. Input and output devices include input sections such as keyboards, mice, etc.; output sections such as cathode ray tubes (CRTs), liquid crystal displays (LCDs), etc. and speakers, etc.; storage sections including hard disks, etc.; The communication part of the network interface card. The memory 802 also stores the following computer instructions to complete the operations specified by the device of the embodiment of the present invention: dividing the delivery area into a plurality of delivery units; establishing an association relationship between the order address and the delivery unit; The multiple order delivery data included in the first order delivery data set are respectively corresponding to multiple delivery units; the statistical information of the order delivery data of each delivery unit is obtained; and based on the statistical information, the multiple delivery units are combined to obtain multiple delivery units. road area

Correspondingly, an embodiment of the present invention provides a computer-readable storage medium, where computer instructions are stored in the computer-readable storage medium, and when the computer instructions are executed, the operations specified in the foregoing method are implemented.

The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions, and operations of the systems, methods, and devices of the embodiments of the present invention, and the blocks on the flowcharts and block diagrams may represent a module, a program segment, or just a segment. Code, the modules, program segments and codes are all executable instructions for implementing specified logical functions. It should also be noted that the executable instructions implementing the specified logical functions may be recombined to create new modules and program segments. Therefore, the blocks and the block sequence of the drawings are only used to better illustrate the process and steps of the embodiment, and should not be taken as a limitation on the invention itself.

Each module or unit of the system can be implemented by hardware, firmware or software. The software includes, for example, coding programs formed in various programming languages such as JAVA, C/C++/C#, and SQL. Although the steps and sequence of the steps in the embodiments of the present invention are given in the method and the method illustration, the executable instructions for implementing the specified logical functions of the steps may be recombined to generate new steps. The sequence of the steps should not be limited only to the sequence of steps in the method and the method legend, and can be adjusted at any time according to functional requirements. For example, some of the steps are performed in parallel or in reverse order.

Systems and methods according to the present invention may be deployed on a single or multiple servers. For example, different modules can be deployed on different servers to form dedicated servers. Alternatively, the same functional unit, module or system can be deployed distributed across multiple servers to reduce load pressure. The servers include, but are not limited to, multiple PCs, PC servers, blade machines, supercomputers, etc. connected in the same local area network and through the Internet.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims (23)

1. A road division method, comprising:

dividing a distribution area into a plurality of distribution units;

establishing an association relation between the order address and the delivery unit;

respectively corresponding a plurality of pieces of order distribution data contained in the first order distribution data set to the plurality of distribution units based on the incidence relation;

acquiring statistical information of order distribution data of each distribution unit; and

and combining the distribution units to obtain a plurality of road areas based on the statistical information.

2. The road division method according to claim 1, further comprising: and checking the order address of the order distribution data contained in the second order distribution data set based on the appropriate GIS data, and taking the order distribution data passing the checking as the order distribution data in the first order distribution data set.

3. The road division method according to claim 2, wherein if an offset between GIS data corresponding to an order address of order distribution data included in the second order distribution data set and the GIS data is smaller than a first set threshold, the order address of the order distribution data in the second order distribution data set is considered to be accurate.

4. The road division method according to claim 1, further comprising:

adopting a GIS technology to carry out forward analysis on the order address of the order distribution data contained in the second order distribution data set to obtain a forward analysis result, and adopting the GIS technology to carry out inverse analysis on the forward analysis result to obtain an inverse analysis address;

verifying the order address of the second order distribution data set by adopting the reverse resolution address; and

and if the similarity between the order address of the order distribution data of the second order distribution data set and the reverse resolution address exceeds a second set threshold, taking the order distribution data with the similarity exceeding the second set threshold as the order distribution data in the first order distribution data set.

5. The road division method according to claim 4, further comprising: and carrying out natural language processing on the reverse analysis address and the order address of the order distribution data of the second order distribution data set.

6. The road division method according to claim 1, further comprising: and acquiring the first order distribution data set from the second order distribution data set according to a first check result of the order address check of the order distribution data of the second order distribution data set by the appropriate GIS data and a second check result of the order address check of the order distribution data of the second order distribution data set by the GIS technology.

7. The road division method according to claim 1, further comprising: and obtaining the appropriate GIS data from the GIS track data of the distribution personnel.

8. The road division method according to claim 1, further comprising: and establishing a corresponding relation between the road areas and the distribution personnel.

9. The road division method of claim 1 wherein the dividing the distribution area into a plurality of distribution units comprises:

converting the order address of the order distribution data contained in the third order distribution data set into corresponding GIS data; and

and dividing the distribution area into a plurality of distribution units according to the corresponding GIS data by adopting a clustering algorithm.

10. The road partitioning method according to claim 9, wherein said clustering algorithm is a k-means algorithm clustering algorithm.

11. The road division method according to claim 9, wherein a time period of order delivery data included in the third order delivery data set is shorter than a time period of order delivery data included in the first order delivery data set.

12. The road division method according to claim 1, further comprising: desensitizing the order delivery data in the first order delivery data set.

13. The road planning method of claim 1, wherein the statistical information is a daily average order number of each delivery unit, and wherein combining the plurality of delivery units to obtain a plurality of road areas based on the statistical information comprises:

and combining the adjacent distribution units together according to the preset road area number and the daily average order number of each distribution unit to form the plurality of road areas.

14. The road planning method according to claim 13, further comprising: providing a visual interface, and dividing the plurality of road areas by dragging the plurality of delivery units on the visual interface.

15. A road zoning system comprising:

the distribution unit dividing module is used for dividing the distribution area into a plurality of distribution units;

the address association module is used for establishing an association relationship between the order address and the delivery unit;

a distribution data corresponding module, configured to respectively correspond, based on the association relationship, a plurality of pieces of order distribution data included in the first order distribution data set to the plurality of distribution units;

the distribution data statistical module is used for acquiring statistical information of the order distribution data of each distribution unit; and

and the distribution unit combination module is used for combining the distribution units to obtain a plurality of road areas based on the statistical information.

16. The road zoning system according to claim 15, further comprising: and the first checking module is used for checking the order address of the order distribution data contained in the second order distribution data set based on the GIS data, and taking the order distribution data passing the checking as the order distribution data in the first order distribution data set.

17. The road zoning system according to claim 15, further comprising: the second checking module is used for carrying out forward analysis on the order address of the order distribution data contained in the second order distribution data set by adopting a GIS technology to obtain a forward analysis result, and carrying out inverse analysis on the forward analysis result by adopting the GIS technology to obtain an inverse analysis address; verifying the order address of the second order distribution data set by adopting the reverse resolution address; and if the similarity between the order address of the order distribution data of the second order distribution data set and the reverse resolution address exceeds a second set threshold, taking the order distribution data with the similarity exceeding the second set threshold as the order distribution data in the first order distribution data set.

18. The road zoning system according to claim 17, further comprising: and the natural language processing module is used for carrying out natural language processing on the reverse analysis address and the order address of the order distribution data of the second order distribution data set.

19. The road zoning system according to claim 15, wherein the delivery unit dividing module comprises:

converting the order address of the order distribution data contained in the third order distribution data set into corresponding GIS data; and

and dividing the distribution area into a plurality of distribution units according to the corresponding GIS data by adopting a clustering algorithm.

20. The road zoning system according to claim 19, wherein a time period of the order delivery data comprised in the third order delivery data set is shorter than a time period of the order delivery data comprised in the first order delivery data set.

21. The road planning system of claim 15 wherein the statistical information is a daily average number of orders per delivery unit, the delivery unit combining module comprising:

and combining the adjacent distribution units together according to the preset road area number and the daily average order number of each distribution unit to form the plurality of road areas.

22. A computer-readable storage medium storing computer instructions which, when executed, implement the road zoning method according to any of the claims 1 to 14.

23. A road division apparatus, characterized by comprising:

a memory for storing computer instructions;

a processor coupled to the memory, the processor configured to perform implementing the road partitioning method of any of claims 1 to 14 based on computer instructions stored by the memory.

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