Commodity retail distribution route planning system based on big data analysis

Abstract

The present invention relates to the field of distribution route planning, and is used to solve the problem that the same logistics company adopts the same distribution route planning algorithm, which cannot adapt to different areas, thus resulting in low distribution efficiency. Specifically, it is a commodity retail distribution route planning system based on big data analysis; in the present invention, the total area covered by the distribution site is divided into multiple sub-areas, and different route planning algorithms are used to calculate one by one, and the route planning algorithms that are more suitable for the distribution sub-areas are continuously replaced, so that the selected route planning algorithm can adapt to the situation in the distribution sub-area, improve the scientificity of route planning, and then improve the distribution efficiency, so that the distribution supervision is more targeted, and at the same time, when dividing the area, the distribution task volume in the area is fully considered, so that the distribution tasks in different areas are averaged as much as possible, and the distribution task load in each area is balanced, so as to facilitate unified management of multiple areas.

Description

Technical Field

[0001] The present invention relates to the field of distribution route planning, and in particular to a commodity retail distribution route planning system based on big data analysis. Background Art

[0002] Route planning is a major link in cargo distribution. Correctly and reasonably arranging distribution routes can effectively reduce transportation costs, save transportation time, and improve customer service levels. Therefore, there have been extensive studies on the planning of logistics distribution routes, but the research direction is limited to intelligent optimization algorithms or improved intelligent optimization algorithms. When using intelligent optimization algorithms for solving problems, it is necessary to first establish a mathematical expression of the optimization problem, that is, the objective function, and set preset conditions to solve it through programming. Although the objective function already has a standard expression, the system in reality is a complex dynamic system, which is difficult to describe using mathematical expressions and it is difficult to accurately consider the randomness and complexity of the actual situation.

[0003] At present, the route planning distribution system in the prior art still has shortcomings. When the existing route planning is used, a logistics system generally adopts the same route planning algorithm. However, for different regions and different road conditions, the same route planning algorithm cannot adapt to the environment of different regions, so that the effect of route planning is uneven, which affects the scientific nature of the distribution route planning. The distribution personnel generally use the planned distribution route as the basis for distribution, which greatly reduces the efficiency of commodity distribution and is not conducive to the promotion and application of the route planning system.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The present invention proposes a commodity retail distribution route planning system based on big data analysis to solve the problem that the same logistics company uses the same distribution route planning algorithm, which cannot adapt to different areas, thus resulting in low distribution efficiency.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A commodity retail distribution route planning system based on big data analysis includes a region division management unit, wherein the region division management unit is used to set a total distribution area and divide the total distribution area into multiple distribution sub-areas;

[0008] A path generation management unit, wherein a plurality of path algorithms are stored in the path generation management unit, and a path algorithm can be selected to calculate a delivery route within a delivery sub-area, and an estimated time for delivery completion is obtained according to the delivery route;

[0009] An execution verification unit, which can collect the delivery path through a satellite positioning system to obtain the actual delivery path, and can also collect the delivery time and record it as the regional completion time;

[0010] A usage management unit, wherein the usage management unit obtains an actual delivery path and a delivery route, compares the delivery route with the actual delivery path, and generates a test valid signal and a test invalid signal;

[0011] A feedback verification unit is used to compare and analyze the delivery time of the delivery partitions, generate an algorithm change signal according to the analysis result, and select a path algorithm.

[0012] As a preferred embodiment of the present invention, the method of dividing the distribution sub-areas by the area division management unit is:

[0013] A total distribution area is selected, and the location of the distribution warehouse is marked in the total distribution area. Starting from the distribution warehouse, multiple lines are extended outward in different directions with the same angle between the multiple lines. Each line is extended to connect with the edge of the total distribution area. The lines are extended along the road as the path, and the area enclosed by the multiple lines is recorded as a group of distribution sub-areas. After the area division management unit completes the division of the distribution sub-areas, it counts the distribution task volume in each distribution sub-area.

[0014] As a preferred implementation of the present invention, the method for the area division management unit to count the amount of distribution tasks is:

[0015] The area division management unit counts the number of residential areas in the distribution area, and the area division management unit counts the historical commodity purchase quantity of each residential area. The statistics are counted on a monthly basis. The area division management unit records the number of residential areas as N, the monthly commodity purchase quantity of each residential area as M, and the size of each residential area as Y. The distribution task volume P is obtained through formula analysis. , where q is the preset weight coefficient, and the value range of q is 10 to 50;

[0016] The area division management unit obtains two groups of delivery task volumes through formula calculation, which are recorded as the delivery task volume peak value P1 and the delivery task volume valley value P2 respectively. The area division management unit compares the delivery task volume peak value P1 with the delivery task volume threshold value. If the delivery task volume peak value P1 is less than the delivery task volume threshold value, the area is recorded as an insufficient delivery task area, and the delivery task volume valley value P2 is compared with the delivery task volume threshold value. If the delivery task volume valley value P2 is greater than the delivery task volume threshold value, the area is recorded as an excessive delivery task area. Otherwise, the area is recorded as a normal delivery task area.

[0017] As a preferred embodiment of the present invention, the area division management unit selects the area where the delivery task exceeds the standard and the area where the delivery task is insufficient, and transfers and divides the residential area in the area where the delivery task exceeds the standard to the adjacent area, and obtains the transferred residential area in the area where the delivery task is insufficient from the adjacent area, until all the delivery sub-areas are the normal delivery task areas;

[0018] If it is impossible to divide all the delivery sub-areas into normal delivery task areas, the delivery task volumes of all the delivery sub-areas are arithmetic averaged and recorded as the average delivery task volume. The delivery sub-areas are then re-divided in the total delivery area according to the average delivery task volume so that the delivery task volume of each delivery sub-area is the same.

[0019] The area division management unit sends the divided delivery sub-areas to the path generation management unit.

[0020] As a preferred embodiment of the present invention, after the path generation management unit obtains the delivery sub-area, it automatically plans the route for the delivery task in the delivery sub-area through the intelligent algorithm, and sends the planned route to the delivery personnel, who deliver according to the planned delivery route. The path management unit stores multiple path intelligent algorithms, and selects one of the path intelligent algorithms for calculation during calculation, and simultaneously calculates the estimated time for delivery completion;

[0021] The route generation management unit sends the delivery route to the use management unit and records it as a predicted delivery route;

[0022] The execution verification unit collects the delivery path through the satellite positioning system on the delivery vehicle and records it as the actual delivery path. The execution verification unit sends the actual delivery path to the usage management unit.

[0023] As a preferred embodiment of the present invention, the usage management unit compares the actual delivery path with the predicted delivery route. If the degree of overlap between the actual delivery path and the predicted delivery route is greater than or equal to a preset value, a prediction valid signal is generated; if the degree of overlap between the actual delivery path and the predicted delivery route is less than the preset value, a test invalid signal is generated.

[0024] As a preferred embodiment of the present invention, after the usage management unit generates the test validity signal, the verification unit collects the delivery completion time of the delivery personnel and records it as the area completion time;

[0025] The feedback verification unit obtains the regional completion time of each delivery sub-area and compares it with the preset delivery time. If the regional completion time of the delivery sub-area is greater than the preset delivery time, a correction accumulation is performed on the area. If the regional completion time of the delivery sub-area is not greater than the preset delivery time, no response is made.

[0026] As a preferred embodiment of the present invention, the feedback verification unit counts the cumulative number of corrections of the delivery sub-area, and when the cumulative number of corrections is greater than a preset value, it is recorded as a correction area;

[0027] The feedback verification unit generates an algorithm change signal and sends it to the path generation management unit. The path generation management unit changes the path algorithm of the correction area and sends the generated new delivery route to the use management unit after the change is completed. The feedback verification unit obtains the area completion time again and compares it with the new preset delivery time. If it is still recorded as a correction area, the path algorithm is changed again until the delivery sub-area is no longer recorded as a correction area.

[0028] If all the routing algorithms used in the distribution sub-area are recorded as the correction area, the feedback verification unit selects the routing algorithm with the shortest area completion time exceeding the preset delivery time.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] 1. In the present invention, when planning the commodity retail route, the total area covered by the distribution site is divided into multiple sub-areas, so that the distribution situation of each sub-area is supervised separately, making the distribution supervision more targeted. At the same time, when dividing the area, the distribution task volume in the area is fully considered, so that the distribution tasks in different areas are as average as possible, and the distribution task load in each area is balanced, which is convenient for unified management of multiple areas.

[0031] 2. In the present invention, when supervising the delivery situation of each area, different route planning algorithms are used for calculation one by one, and they are constantly replaced to find a route planning algorithm that is more suitable for the delivery sub-area, so that the selected route planning algorithm can adapt to the actual situation in the delivery sub-area, improve the scientific nature of route planning, and thus improve the delivery efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0033] Figure 1 is a system block diagram of the present invention;

[0034] Figure 2 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0035] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] Example 1: Please refer to Figure 1 - Figure 2 As shown in FIG. 1 , a commodity retail distribution route planning system based on big data analysis includes a region division management unit, a path generation management unit, a usage management unit, an execution verification unit, and a feedback verification unit. The region division management unit obtains the total distribution area by manual input and divides the total distribution area into i distribution sub-areas. The method for dividing the distribution sub-areas by the region division management unit is:

[0037] Select a general distribution area, mark the location of the distribution warehouse in the general distribution area, take the distribution warehouse as the starting point, extend multiple lines in different directions outward, and the angles between the multiple lines are the same. Extend each line to connect with the edge of the general distribution area. The lines are extended along the road as the path. The area enclosed by the multiple lines is recorded as a group of distribution sub-areas, where the lines extending outward are determined according to the number of delivery personnel in the distribution warehouse;

[0038] After completing the division of the distribution sub-areas, the regional division management unit counts the distribution task volume in each distribution sub-area. The method for the regional division management unit to count the distribution task volume is:

[0039] The regional division management unit counts the number of residential areas in the distribution area, where the residential area refers to residential areas such as communities and apartments. The regional division management unit counts the historical commodity purchase quantity of each residential area. The statistics are made on a monthly basis. The regional division management unit records the number of residential areas as N, the monthly commodity purchase quantity of each residential area as M, and the size of each residential area as Y. The distribution task volume P is obtained through formula analysis. , where q is the preset weight coefficient, and the value range of q is 10 to 50;

[0040] The regional division management unit obtains two groups of delivery task volumes through formula calculation, which are recorded as the delivery task volume peak value P1 and the delivery task volume valley value P2 respectively. The regional division management unit compares the delivery task volume peak value P1 with the delivery task volume threshold value. If the delivery task volume peak value P1 is less than the delivery task volume threshold value, a delivery task volume insufficient signal is generated, and the area is recorded as a delivery task insufficient area. The delivery task volume valley value P2 is compared with the delivery task volume threshold value. If the delivery task volume valley value P2 is greater than the delivery task volume threshold value, a delivery task volume excessive signal is generated, and the area is recorded as a delivery task excessive area. Otherwise, a delivery task volume normal signal is generated, and the area is recorded as a delivery task normal area.

[0041] The area division management unit selects the area where the delivery task exceeds the standard and the area where the delivery task is insufficient, and transfers and divides the residential areas in the area where the delivery task exceeds the standard to the adjacent area, and obtains the transferred residential areas in the area where the delivery task is insufficient from the adjacent area, until all the delivery sub-areas are the normal delivery task areas;

[0042] If it is impossible to divide all the delivery sub-areas into normal delivery task areas, the delivery task quantities of all the delivery sub-areas shall be arithmetic averaged and recorded as the average delivery task quantity. The delivery sub-areas shall be re-divided in the total delivery area according to the average delivery task quantity so that the delivery task quantity of each delivery sub-area is the same.

[0043] The area division management unit sends the divided delivery sub-areas to the path generation management unit.

[0044] Example 2: Please refer to Figure 1 - Figure 2 As shown, after the path generation management unit obtains the distribution sub-area, it automatically plans the route for the distribution task in the distribution sub-area through the intelligent algorithm, and sends the planned route to the delivery personnel, who deliver according to the planned delivery route. The path management unit stores multiple path intelligent algorithms, and selects one of the path intelligent algorithms for calculation during calculation, and calculates the estimated time for delivery completion at the same time;

[0045] The route generation management unit sends the delivery route to the use management unit and records it as a predicted delivery route;

[0046] The execution verification unit collects the delivery path through the satellite positioning system on the delivery vehicle and records it as the actual delivery path. The execution verification unit sends the actual delivery path to the use management unit;

[0047] The management unit is used to compare the actual delivery path with the predicted delivery route. If the overlap between the actual delivery path and the predicted delivery route is greater than or equal to a preset value, a prediction valid signal is generated. If the overlap between the actual delivery path and the predicted delivery route is less than a preset value, a test invalid signal is generated.

[0048] After the test valid signal is generated, the execution verification unit collects the delivery completion time of the delivery personnel and records it as the regional completion time;

[0049] The feedback verification unit obtains the regional completion time of each delivery sub-area and compares it with the preset delivery time. If the regional completion time of the delivery sub-area is greater than the preset delivery time, a correction accumulation is performed on the area. If the regional completion time of the delivery sub-area is not greater than the preset delivery time, no response is made.

[0050] The feedback verification unit counts the cumulative number of corrections in the distribution sub-area, and when the cumulative number of corrections is greater than a preset value, it is recorded as a correction area;

[0051] The feedback verification unit generates an algorithm change signal and sends it to the path generation management unit. The path generation management unit changes the path algorithm of the correction area and sends the generated new delivery route to the use management unit after the change is completed. The feedback verification unit obtains the area completion time again and compares it with the new preset delivery time. If it is still recorded as a correction area, the path algorithm is changed again until the delivery sub-area is no longer recorded as a correction area.

[0052] If all the routing algorithms used in the distribution sub-area are recorded as the correction area, the feedback verification unit selects the routing algorithm with the shortest area completion time exceeding the preset delivery time.

[0053] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A commodity retail distribution route planning system based on big data analysis, characterized in that: It includes a region division management unit, which is used to set a total distribution area and divide the total distribution area into multiple distribution sub-areas; A path generation management unit, wherein a plurality of path algorithms are stored in the path generation management unit, and a path algorithm can be selected to calculate a delivery route within a delivery sub-area, and an estimated time for delivery completion is obtained according to the delivery route; An execution verification unit, which can collect the delivery path through a satellite positioning system to obtain the actual delivery path, and can also collect the delivery time and record it as the regional completion time; A usage management unit, wherein the usage management unit obtains an actual delivery path and a delivery route, compares the delivery route with the actual delivery path, and generates a test valid signal and a test invalid signal; A feedback verification unit, the feedback verification unit is used to compare and analyze the delivery time of the delivery partitions, generate an algorithm change signal according to the analysis result, and select a path algorithm; The method for dividing the distribution sub-areas by the area division management unit is: A distribution general area is selected, and the location of the distribution warehouse is marked in the distribution general area. A plurality of lines are extended outward in different directions with the distribution warehouse as the starting point, and the angles between the plurality of lines are the same. Each line is extended to connect with the edge of the distribution general area, and the lines are extended along the road as the path. The area enclosed by the connection of the plurality of lines is recorded as a group of distribution sub-areas. After the distribution sub-areas are divided, the area division management unit counts the amount of distribution tasks in each distribution sub-area. The method for the regional division management unit to count the distribution task volume is: The area division management unit counts the number of residential areas in the distribution area, and the area division management unit counts the historical commodity purchase quantity of each residential area. The statistics are counted on a monthly basis. The area division management unit records the number of residential areas as N, the monthly commodity purchase quantity of each residential area as M, and the size of each residential area as Y. The distribution task volume P is obtained through formula analysis. , where q is the preset weight coefficient, and the value range of q is 10 to 50; The area division management unit obtains two groups of delivery task volumes through formula calculation, which are recorded as the delivery task volume peak value P1 and the delivery task volume valley value P2 respectively. The area division management unit compares the delivery task volume peak value P1 with the delivery task volume threshold value. If the delivery task volume peak value P1 is less than the delivery task volume threshold value, the area is recorded as an insufficient delivery task area, and the delivery task volume valley value P2 is compared with the delivery task volume threshold value. If the delivery task volume valley value P2 is greater than the delivery task volume threshold value, the area is recorded as an excessive delivery task area. Otherwise, the area is recorded as a normal delivery task area.

2. The commodity retail distribution route planning system based on big data analysis according to claim 1 is characterized in that: The area division management unit selects areas where the delivery task exceeds the standard and areas where the delivery task is insufficient, and transfers and divides the residential areas in the areas where the delivery task exceeds the standard to adjacent areas, and obtains the transferred residential areas in the areas where the delivery task is insufficient from adjacent areas, until all the delivery sub-areas are areas where the delivery task is normal; If it is impossible to divide all the delivery sub-areas into normal delivery task areas, the delivery task volumes of all the delivery sub-areas are arithmetic averaged and recorded as the average delivery task volume. The delivery sub-areas are then re-divided in the total delivery area according to the average delivery task volume so that the delivery task volume of each delivery sub-area is the same. The area division management unit sends the divided delivery sub-areas to the path generation management unit.

3. The commodity retail distribution route planning system based on big data analysis according to claim 2 is characterized in that: After the path generation management unit obtains the distribution sub-area, it automatically plans the route for the distribution task in the distribution sub-area through the intelligent algorithm, and sends the planned route to the distribution personnel, who distribute the goods according to the planned distribution route. The path management unit stores multiple path intelligent algorithms, and selects one of the path intelligent algorithms for calculation during calculation, and calculates the estimated time for delivery completion at the same time; The route generation management unit sends the delivery route to the use management unit and records it as a predicted delivery route; The execution verification unit collects the delivery path through the satellite positioning system on the delivery vehicle and records it as the actual delivery path. The execution verification unit sends the actual delivery path to the use management unit.

4. The commodity retail distribution route planning system based on big data analysis according to claim 3 is characterized in that: The usage management unit compares the actual delivery path with the predicted delivery route. If the degree of overlap between the actual delivery path and the predicted delivery route is greater than or equal to a preset value, a prediction valid signal is generated. If the degree of overlap between the actual delivery path and the predicted delivery route is less than the preset value, a test invalid signal is generated.

5. The commodity retail distribution route planning system based on big data analysis according to claim 4 is characterized in that: After the usage management unit generates the test validity signal, the execution verification unit collects the delivery completion time of the delivery personnel and records it as the regional completion time; The feedback verification unit obtains the regional completion time of each delivery sub-area and compares it with the preset delivery time. If the regional completion time of the delivery sub-area is greater than the preset delivery time, a correction accumulation is performed on the area. If the regional completion time of the delivery sub-area is not greater than the preset delivery time, no response is made.

6. The commodity retail distribution route planning system based on big data analysis according to claim 5 is characterized in that: The feedback verification unit counts the cumulative number of corrections of the delivery sub-area, and when the cumulative number of corrections is greater than a preset value, it is recorded as a correction area; The feedback verification unit generates an algorithm change signal and sends it to the path generation management unit. The path generation management unit changes the path algorithm of the correction area and sends the generated new delivery route to the use management unit after the change is completed. The feedback verification unit obtains the area completion time again and compares it with the new preset delivery time. If it is still recorded as a correction area, the path algorithm is changed again until the delivery sub-area is no longer recorded as a correction area. If all the routing algorithms used in the distribution sub-area are recorded as the correction area, the feedback verification unit selects the routing algorithm with the shortest area completion time exceeding the preset delivery time.

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