A logistics transportation route optimization method and system

Abstract

The present application provides a method and system for optimizing logistics transportation routes, and relates to the technical field of route optimization. The method includes: a logistics management system fits a forward route and receives a reverse logistics request. A road network model is constructed, the requested route and time window are matched, and a transportation route with a high degree of overlap is obtained. Through a two-way transportation route optimization model, an optimized two-way route is output. Two-way logistics is performed according to this route. The present application can solve the problem that the prior art cannot effectively integrate the information of forward logistics and reverse logistics, resulting in the transportation resources not being optimally utilized, further affecting the overall efficiency of logistics transportation. It can ensure that the logistics transportation tasks are completed efficiently and on time according to the two-way transportation route, which not only improves the logistics efficiency and reduces the cost, but also enhances the market competitiveness and customer satisfaction of the enterprise.

Description

Technical Field

[0001] The present application relates to the technical field of route optimization, and in particular to a method and system for optimizing logistics transportation routes. Background Art

[0002] With the development of information technology, especially the application of technologies such as big data, cloud computing, and artificial intelligence, methods for optimizing logistics and transportation routes are also constantly improving.

[0003] At present, the existing logistics and transportation management systems often adopt independent optimization methods when dealing with forward logistics and reverse logistics. This leads to unreasonable resource allocation, increases logistics costs, reduces transportation efficiency, and may affect customer satisfaction.

[0004] In summary, the existing technology cannot effectively integrate the information of forward logistics and reverse logistics, resulting in the failure to optimally utilize transportation resources, further affecting the overall efficiency of logistics transportation. Summary of the invention

[0005] The purpose of this application is to provide a logistics transportation route optimization method and system to solve the problem that the existing technology cannot effectively integrate the information of forward logistics and reverse logistics, resulting in the transportation resources not being optimally utilized, further affecting the overall efficiency of logistics transportation.

[0006] In view of the above problems, the present application provides a method and system for optimizing logistics transportation routes.

[0007] In a first aspect, the present application provides a method for optimizing a logistics and transportation route, which is implemented through a logistics and transportation route optimization system, wherein the method includes: an interactive logistics and transportation management system, fitting a forward logistics route set; receiving first reverse logistics information, collecting requested logistics route information and requested logistics time information of the first reverse logistics information; constructing a road network model based on the forward logistics route set; inputting the requested logistics route information into the road network model for route overlap matching, and obtaining N identified transportation routes with route overlap greater than a preset route overlap; inputting the requested logistics time information into the road network model for time window overlap matching, and obtaining M identified transportation routes with time window overlap greater than a preset time window overlap; establishing a two-way transportation route optimization model, inputting the N identified transportation routes and the M identified transportation routes into the two-way transportation route optimization model, and outputting a two-way transportation route; the logistics and transportation management system performs two-way logistics transportation according to the two-way transportation route.

[0008] In a second aspect, the present application further provides a logistics and transportation route optimization system for executing a logistics and transportation route optimization method as described in the first aspect, wherein the system includes: a route set acquisition module for interacting with a logistics and transportation management system to fit a forward logistics route set; a message receiving module for receiving first reverse logistics information and collecting requested logistics route information and requested logistics time information of the first reverse logistics information; a road network model construction module for constructing a road network model according to the forward logistics route set; an overlapping matching module for inputting the requested logistics route information into the road network model for route overlapping matching, and obtaining N identified transportation routes with route overlapping degrees greater than a preset route overlapping degree; an overlapping judgment module for inputting the requested logistics time information into the road network model for time window overlapping matching, and obtaining M identified transportation routes with time window overlapping degrees greater than a preset time window overlapping degree; a two-way transportation route output module for establishing a two-way transportation route optimization model, inputting the N identified transportation routes and the M identified transportation routes into the two-way transportation route optimization model, and outputting a two-way transportation route; a two-way transportation module, wherein the logistics and transportation management system performs two-way logistics transportation according to the two-way transportation route.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] Through the interactive logistics and transportation management system, a forward logistics route set is fitted; the first reverse logistics information is received, and the requested logistics route information and requested logistics time information of the first reverse logistics information are collected; according to the forward logistics route set, a road network model is constructed; the requested logistics route information is input into the road network model for route overlapping matching, and N identified transportation routes with route overlapping degrees greater than the preset route overlapping degrees are obtained; according to the requested logistics time information, the road network model is input for time window overlapping matching, and M identified transportation routes with time window overlapping degrees greater than the preset time window overlapping degrees are obtained; a two-way transportation route optimization model is established, and the N identified transportation routes and the M identified transportation routes are input into the two-way transportation route optimization model to output a two-way transportation route; the logistics and transportation management system performs two-way logistics transportation according to the two-way transportation route, which effectively solves the problem that the prior art cannot effectively integrate the information of forward logistics and reverse logistics, resulting in the transportation resources not being optimally utilized, further affecting the overall efficiency of logistics transportation, and can ensure that the logistics transportation tasks are completed efficiently and on time according to the two-way transportation routes, which not only improves the logistics efficiency and reduces the cost, but also enhances the market competitiveness and customer satisfaction of the enterprise.

[0011] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0013] Figure 1 A flow chart of a method for optimizing logistics transportation routes for this application;

[0014] Figure 2 The present invention is a structural schematic diagram of a logistics transportation route optimization system for the present invention.

[0015] Description of reference numerals:

[0016] Route set acquisition module 11, message receiving module 12, road network model construction module 13, overlap matching module 14, overlap degree judgment module 15, two-way transportation route output module 16, two-way transportation module 17. DETAILED DESCRIPTION

[0017] The present application provides a method and system for optimizing logistics transportation routes, thereby solving the problem that the prior art cannot effectively integrate the information of forward logistics and reverse logistics, resulting in the transportation resources not being optimally utilized, further affecting the overall efficiency of logistics transportation. It can ensure that the logistics transportation tasks are completed efficiently and on time according to the two-way transportation routes, which not only improves the logistics efficiency and reduces the cost, but also enhances the market competitiveness and customer satisfaction of the enterprise.

[0018] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0019] Embodiment 1

[0020] Please refer to the attached Figure 1 The present application provides a method for optimizing a logistics transportation route, wherein the method is applied to a logistics transportation route optimization system, and the method specifically comprises the following steps:

[0021] S1: Interactive logistics transportation management system, fitting forward logistics route set.

[0022] Specifically, all forward logistics route information is collected, including the starting point, end point, transportation time, cargo type, transportation tool, etc. When a reverse logistics request is received, the requested logistics route information and time information are collected.

[0023] S2: Receive the first reverse logistics information, and collect the requested logistics route information and requested logistics time information of the first reverse logistics information.

[0024] Specifically, information is received through API interfaces, Web services, electronic data interchange, etc. Reverse logistics information includes return requests, recycling requests, or repair requests for goods, etc. Route information includes the starting point and destination of the goods, as well as any intermediate stations or specific transportation path requirements. Time information includes the available time window for the goods, the expected delivery time, or any other time-related constraints.

[0025] S3: constructing a road network model according to the forward logistics route set;

[0026] Specifically, in the road network model, nodes represent various points in the logistics network, such as warehouses, distribution centers, retail outlets, or customer locations. Edges represent paths or transportation routes connecting these nodes, and edges can have weights, such as distance, transportation time, cost, etc. Collect actual data on forward logistics routes, including starting points, end points, transportation time, frequency, capacity constraints, etc. Use methods from graph theory to construct a network graph in which the relationship between nodes and edges is clearly defined. Assign weights to each edge in the network graph based on actual logistics cost and time data. The allocation of weights should reflect the actual logistics operations, including factors such as traffic conditions, route quality, and cargo type. Consider various constraints in the road network model, such as vehicle capacity, working hours, cargo type restrictions, etc. These constraints will affect the final transportation route selection and optimization results. After the model is built, it is verified to ensure that it can accurately reflect the characteristics and operating rules of the logistics network. Based on the results of the verification, the model is adjusted and optimized to improve the accuracy and practicality of its predictions.

[0027] S4: Input the requested logistics route information into the road network model for route overlap matching, and obtain N identified transport routes whose route overlap is greater than a preset route overlap.

[0028] Specifically, the collected route information of the reverse logistics request is input into the constructed road network model. This information includes the starting point, destination and any other specific route requirements of the goods. An algorithm is used to calculate the overlap between the input reverse logistics route and the existing forward logistics route in the road network model. The overlap can be determined by comparing the nodes and edges of the route, or it can be evaluated by calculating the similarity or distance between the routes. A preset route overlap threshold is set by a technician in this field. This threshold determines which routes are considered to have sufficient overlap. Based on the calculated route overlap and the preset threshold, the forward logistics routes with an overlap greater than the threshold are screened out. All qualified identified transport routes will be output, and the number of these routes is N. The output result can be a list, a set or other suitable data structure.

[0029] S5: Input the road network model according to the requested logistics time information to perform time window overlap matching, and obtain M identified transportation routes whose time window overlap is greater than a preset time window overlap.

[0030] Specifically, the time information of the collected reverse logistics requests is input into the road network model. This information includes the available time window of the goods, the expected delivery time or other time-related constraints. An algorithm is used to calculate the overlap between the input reverse logistics time window and the existing forward logistics route time window in the road network model. The overlap calculation can take into account the start and end time of the time window, as well as any possible flexibility or buffer time. A preset time window overlap threshold is set by a technician in this field. This threshold determines which time windows are considered to be sufficiently overlapping. According to the calculated time window overlap and the preset threshold, the forward logistics routes with an overlap greater than the threshold are screened out. All identified transport routes with overlapping time windows that meet the conditions will be output, and the number of these routes is M. The output result can be a list, a set or other suitable data structure.

[0031] S6: Establish a bidirectional transport route optimization model, input the N identified transport routes and the M identified transport routes into the bidirectional transport route optimization model, and output a bidirectional transport route.

[0032] Specifically, determine the objective function of the optimization model, such as minimizing the total transportation cost, minimizing the total transportation time, or maximizing the transportation efficiency. The objective function will be defined based on the weights of the routes, such as distance, time, cost, etc. and possible penalty factors, for the cost of violating the constraints. Integrate the N identified transportation routes obtained by overlapping matching of routes and the M identified transportation routes obtained by overlapping matching of time windows. These routes will become the input of the optimization model for building a two-way transportation solution. Use mathematical modeling techniques such as linear programming, integer programming, network flow model, etc. to establish a two-way transportation route optimization model. The model contains all relevant constraints, such as vehicle capacity, working hours, cargo type restrictions, etc. According to the complexity and scale of the model, select an optimization algorithm, such as genetic algorithm, simulated annealing algorithm, ant colony algorithm, etc. Solve the optimization model using the selected algorithm to find the optimal or approximately optimal two-way transportation route. To find a solution that satisfies all constraints and has the optimal objective function. Once the optimization model is solved, a detailed plan of the two-way transportation route will be output. The output includes the specific path of each route, the transportation resources used, the estimated departure and arrival times, etc.

[0033] S7: The logistics transportation management system performs two-way logistics transportation according to the two-way transportation route.

[0034] Specifically, according to the two-way transportation route output by the optimization model, necessary transportation resources such as vehicles, containers, drivers, etc. are allocated. Ensure that the allocated resources meet the route requirements, such as cargo type, capacity, time window, etc. Generate specific transportation scheduling instructions based on the plan of the two-way transportation route. The instructions include detailed loading, transportation, unloading schedules and route guides. Make necessary adjustments to the transportation plan based on real-time monitoring data and other dynamic information, such as traffic conditions, cargo changes, etc. Dynamic adjustments can ensure that the transportation process always meets the optimization requirements.

[0035] Furthermore, step S6 of the present application also includes:

[0036] The two-way transport route optimization model uses the N identified transport routes and the M identified transport routes as the initialization population to generate an initial solution space set; uses route overlap and time window overlap as feature vectors to vector-identify each route in the solution space set, and outputs the identified initial solution space set; performs feature fitness evaluation on the identified initial solution space set to obtain a fitness set; performs optimization in the fitness set, outputs a first optimized transport route, and outputs the first optimized transport route as a two-way transport route.

[0037] Specifically, N identified transport routes with high route overlap and M identified transport routes with high time window overlap are used as the initial population. The initial population is a subset of the solution space, representing possible transport route combinations. Using route overlap and time window overlap as feature vectors, each route in the initial population is vector-identified. Vector identification helps to distinguish different solutions in the solution space and provides a basis for subsequent fitness evaluation. Feature fitness evaluation is performed on each route in the identified initial solution space set. The fitness function is designed based on optimization objectives, such as cost minimization, time minimization, etc., which measures the pros and cons of each solution. According to the fitness evaluation results, a fitness set is constructed, which contains all evaluated solutions and their fitness values. Optimization is performed in the fitness set, that is, searching for the solution with the highest fitness. The optimization process can include operations such as selection, crossover, and mutation. The solution with the highest fitness found in the optimization process is output as the first optimized transport route. This solution represents the optimal or approximately optimal bidirectional transport route found in the current iteration. Repeat the above process and continuously improve the solution through multiple rounds of iterations. The final output is the optimal or approximately optimal two-way transportation route found after multiple iterations.

[0038] Furthermore, the present application also includes:

[0039] Determine whether the fitness set includes a solution greater than or equal to a preset fitness; if it does not include a solution greater than or equal to the preset fitness, generate a cross-line group, wherein the cross-line group is obtained by taking two lines as a group; perform crossover according to the cross-line group to generate an expanded solution space set; and update the initial solution space set according to the expanded solution space set.

[0040] Specifically, it is checked whether the fitness set includes solutions greater than or equal to the preset fitness. The preset fitness is a threshold used to determine whether the quality of the solution meets the business requirements. If the fitness set does not include a solution that meets the preset fitness, a cross line group is generated. The cross line group is composed of two lines in the solution space, which will be used for crossover operations to generate new solutions. The lines in the cross line group are used for crossover operations. New solutions are generated by exchanging part of the line information. After the crossover operation, the generated new solution is added to the expanded solution space set. The expanded solution space set contains the original solution and the new solution generated by the crossover operation. The initial solution space set is updated using the expanded solution space set. The update includes replacing, merging, or expanding the initial solution space set to include a better solution.

[0041] Furthermore, the present application also includes:

[0042] Perform cross entropy identification on each group of cross lines in the cross line group, and output a cross entropy index corresponding to each cross line group; wherein the cross entropy index is an entropy value assigned to identify the cross effect of each group of cross lines, and the cross entropy identification includes identifying the line overlap complementarity and window synchronization of each group of cross lines; according to the cross entropy index, identify the cross lines that are greater than or equal to the preset cross entropy index. A cross-line group; based on the The cross nodes of the cross line groups are crossed to generate a cross solution space set.

[0043] Specifically, for each group of cross-circuit lines in the cross-circuit group, cross-entropy identification is performed. The cross-entropy index is an indicator to measure the cross-circuit effect of each group of cross-circuit lines, which takes into account the line overlap complementarity and window synchronization. Evaluate the degree of overlap of two lines in nodes and edges, as well as their functional complementarity. High overlap complementarity means that the two lines have good synergy in resource utilization and task execution. Evaluate the degree of synchronization of the two lines in the time window, that is, whether their schedules match. High window synchronization means that the two lines can be well connected in time, reducing waiting time. Output a cross-entropy indicator value for each group of cross-circuit lines, which reflects the potential effect of the cross. According to the preset cross-entropy indicator threshold , identify those cross entropy metrics greater than or equal to The crossover line group. In the identified valid crossover line group, the crossover node is selected for the crossover operation. The crossover operation generates a new line by exchanging the segments after the crossover node of the parent line. The new line generated by the crossover operation is added to the crossover solution space set. This set contains the new solutions generated by the crossover operation, which will be used for the next round of fitness evaluation and selection.

[0044] Further, if there is no solution with a fitness greater than or equal to the preset fitness, identify a solution with a fitness less than the preset cross entropy index. A cross-line group, based on the The mutation nodes of the cross line groups are randomly mutated to generate a set of mutation solution spaces; and an expanded solution space set is generated according to the cross solution space set and the set of mutation solution spaces.

[0045] Specifically, if the fitness set does not include a solution with a fitness greater than or equal to the preset fitness, then identify a solution with a fitness less than the preset cross entropy index Crossover line groups. These line groups may not have good crossover characteristics and therefore need to be improved through mutation operations. Among the identified crossover line groups with low cross entropy indicators, mutation nodes are selected for random mutation. Mutation operations can generate new lines by randomly changing certain parts of the line, such as exchanging nodes, flipping line segments, etc. The new lines generated by the mutation operation are added to the mutation solution space set. This set contains new solutions generated by mutation operations, which will be used to increase the diversity of the population. The crossover solution space set and the mutation solution space set are combined to generate an expanded solution space set. The expanded solution space set contains the original solution, the new solution generated by the crossover operation, and the new solution generated by the mutation operation.

[0046] Furthermore, the present application also includes:

[0047] Obtaining a node set and an edge set of each route in the road network model; obtaining overlapping nodes and overlapping edges of each route in the node set and the edge set according to the requested logistics route information;

[0048] The line overlap degree is obtained based on the proportion of overlapping nodes and overlapping edges of each line.

[0049] Specifically, the node set and edge set of all routes are obtained from the road network model. Based on the logistics route information of the reverse logistics request, the overlapping nodes and edges are searched in the node set and edge set. Overlapping nodes refer to nodes that appear in both the forward logistics route and the reverse logistics request, and overlapping edges refer to edges connecting these overlapping nodes. For each forward logistics route, the number of overlapping nodes and overlapping edges is calculated. The overlap degree is calculated based on the proportion of overlapping nodes and edges in the total nodes and edges. For example, if a route has 10 nodes, 2 of which overlap with the reverse logistics request, then the overlap degree may be 20%. Based on the calculated proportion of overlapping nodes and overlapping edges, an overlap degree value is generated for each forward logistics route. The overlap degree value reflects the similarity between the route and the reverse logistics request in terms of nodes and edges. The overlap degree value of each route is output.

[0050] Furthermore, the present application also includes:

[0051] Obtain the time window of each route in the road network model; create a time window list to store the time window of each route in the road network model; sort the time window list according to the start time of each route, and obtain the overlapping window time period of the time window of each route and the time window of the requested logistics time information by scanning the sorted time window list, and output the time window overlap degree based on the proportion of the overlapping window time period to the total time period of the route.

[0052] Specifically, obtain the time window information for each route from the road network model. This information includes the route's start time, end time, any specific time window restrictions, etc. Create a time window list to store the time window for each route in the road network model. Each element in the list may be a tuple or object containing the start time and end time. Sort the time window list according to the start time of each route. The sorted list is arranged in the order of the route's start time to facilitate subsequent time window overlap matching. Scan the sorted time window list to find window time periods that overlap with the time window for requesting logistics time information. Overlapping window time periods refer to time periods where two time windows overlap, that is, there is at least one common time point. For each route, calculate the overlapping window time period of its time window and the time window for requesting logistics time information. The time window overlap is usually the proportion of the overlapping window time period to the total time period of the route. For example, if the total time period of a route is 10 hours, of which the overlapping time period with the requesting logistics time information is 2 hours, then the time window overlap is 20%. Output the time window overlap of each route.

[0053] Furthermore, the present application also includes:

[0054] A reverse logistics information set within a preset area is obtained, node frequency is identified according to a bidirectional transportation route set corresponding to the reverse logistics information set, and a reverse transit node is set, wherein the reverse transit node is a route node with the largest node frequency in the bidirectional transportation route set; the logistics transportation management system uses the reverse transit node to perform transit management on the preset area.

[0055] Specifically, reverse logistics information is collected from the preset area, which includes requirements for returns, recycling, and repairs. Reverse logistics information includes the starting location, destination, type, quantity, and time requirements of the goods. Based on the forward logistics route set and reverse logistics information, two-way transportation routes that can share transportation resources are identified. These routes are determined by cross-matching, time window matching, and other methods. The nodes in the two-way transportation route set are frequency identified, and the number of occurrences of each node in all routes is calculated. Frequency identification can help determine which nodes have a high frequency of use and importance in the logistics network. According to the node frequency identification results, reverse transit nodes are set. Reverse transit nodes are the route nodes with the highest node frequency in the two-way transportation route set, and are usually located in the preset area. The logistics transportation management system takes the reverse transit node as the core and performs transit management on the preset area. Transit management includes centralized processing, sorting, packaging, loading and unloading of reverse logistics, as well as docking and transfer operations of forward logistics. Through the management of reverse transit nodes, the logistics process is optimized, transportation costs are reduced, and transportation efficiency is improved. The reverse transit node can serve as a key node in the logistics network to improve the performance of the entire logistics network.

[0056] In summary, the logistics transportation route optimization method provided by this application has the following technical effects:

[0057] Through the interactive logistics and transportation management system, a forward logistics route set is fitted; the first reverse logistics information is received, and the requested logistics route information and requested logistics time information of the first reverse logistics information are collected; according to the forward logistics route set, a road network model is constructed; the requested logistics route information is input into the road network model for route overlapping matching, and N identified transportation routes with route overlapping degrees greater than the preset route overlapping degrees are obtained; according to the requested logistics time information, the road network model is input for time window overlapping matching, and M identified transportation routes with time window overlapping degrees greater than the preset time window overlapping degrees are obtained; a two-way transportation route optimization model is established, and the N identified transportation routes and the M identified transportation routes are input into the two-way transportation route optimization model to output a two-way transportation route; the logistics and transportation management system performs two-way logistics transportation according to the two-way transportation route, which effectively solves the problem that the prior art cannot effectively integrate the information of forward logistics and reverse logistics, resulting in the transportation resources not being optimally utilized, further affecting the overall efficiency of logistics transportation, and can ensure that the logistics transportation tasks are completed efficiently and on time according to the two-way transportation routes, which not only improves the logistics efficiency and reduces the cost, but also enhances the market competitiveness and customer satisfaction of the enterprise.

[0058] Embodiment 2

[0059] Based on the same inventive concept as the logistics transportation route optimization method in the aforementioned embodiment, the present application also provides a logistics transportation route optimization system, please refer to the attached Figure 2 , the system comprising:

[0060] The route set acquisition module 11 is used for interacting with the logistics transportation management system and fitting the forward logistics route set.

[0061] The message receiving module 12 is used to receive the first reverse logistics information, and collect the requested logistics route information and requested logistics time information of the first reverse logistics information.

[0062] The road network model building module 13 is used to build a road network model according to the forward logistics route set.

[0063] The overlapping matching module 14 is used to input the requested logistics route information into the road network model to perform route overlapping matching, and obtain N identified transport routes whose route overlapping degrees are greater than a preset route overlapping degree.

[0064] The overlap judgment module 15 is used to input the road network model according to the requested logistics time information to perform time window overlap matching, and obtain M identified transportation routes whose time window overlap is greater than the preset time window overlap.

[0065] The bidirectional transport route output module 16 is used to establish a bidirectional transport route optimization model, input the N identified transport routes and the M identified transport routes into the bidirectional transport route optimization model, and output a bidirectional transport route.

[0066] The bidirectional transportation module 17, the logistics transportation management system performs bidirectional logistics transportation according to the bidirectional transportation route.

[0067] Furthermore, the bidirectional transport line output module 16 in the system is also used for:

[0068] The two-way transport route optimization model uses the N identified transport routes and the M identified transport routes as the initialization population to generate an initial solution space set; uses route overlap and time window overlap as feature vectors to vector-identify each route in the solution space set, and outputs the identified initial solution space set; performs feature fitness evaluation on the identified initial solution space set to obtain a fitness set; performs optimization in the fitness set, outputs a first optimized transport route, and outputs the first optimized transport route as a two-way transport route.

[0069] Furthermore, the system further comprises a solution updating module, wherein the solution updating module is used for:

[0070] Determine whether the fitness set includes a solution greater than or equal to a preset fitness; if it does not include a solution greater than or equal to the preset fitness, generate a cross-line group, wherein the cross-line group is obtained by taking two lines as a group; perform crossover according to the cross-line group to generate an expanded solution space set; and update the initial solution space set according to the expanded solution space set.

[0071] Furthermore, the system further comprises a cross-space set acquisition module, and the cross-space set acquisition module is used to:

[0072] Perform cross entropy identification on each group of cross lines in the cross line group, and output a cross entropy index corresponding to each cross line group; wherein the cross entropy index is an entropy value assigned to identify the cross effect of each group of cross lines, and the cross entropy identification includes identifying the line overlap complementarity and window synchronization of each group of cross lines; according to the cross entropy index, identify the cross lines that are greater than or equal to the preset cross entropy index. A cross-line group; based on the The cross nodes of the cross line groups are crossed to generate a cross solution space set.

[0073] Furthermore, the system further comprises an expanded solution space set acquisition module, wherein the expanded solution space set acquisition module is used to:

[0074] If there is no solution with a fitness greater than or equal to the preset fitness, identify a solution with a fitness less than the preset cross entropy index. A cross-line group, based on the The mutation nodes of the cross line groups are randomly mutated to generate a set of mutation solution spaces; and an expanded solution space set is generated according to the cross solution space set and the set of mutation solution spaces.

[0075] Furthermore, the system further comprises a line overlap acquisition module, and the line overlap acquisition module is used to:

[0076] Obtain the node set and edge set of each route in the road network model; obtain the overlapping nodes and overlapping edges of each route in the node set and the edge set according to the requested logistics route information; and obtain the route overlap degree according to the proportion of overlapping nodes and overlapping edges of each route.

[0077] Furthermore, the system further comprises a window overlap acquisition module, and the window overlap acquisition module is used to:

[0078] Obtain the time window of each route in the road network model; create a time window list to store the time window of each route in the road network model; sort the time window list according to the start time of each route, and obtain the overlapping window time period of the time window of each route and the time window of the requested logistics time information by scanning the sorted time window list, and output the time window overlap degree based on the proportion of the overlapping window time period to the total time period of the route.

[0079] Furthermore, the system further includes a transfer management module, which is used to:

[0080] A reverse logistics information set within a preset area is obtained, node frequency is identified according to a bidirectional transportation route set corresponding to the reverse logistics information set, and a reverse transit node is set, wherein the reverse transit node is a route node with the largest node frequency in the bidirectional transportation route set; the logistics transportation management system uses the reverse transit node to perform transit management on the preset area.

[0081] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. Figure 1 The logistics transportation route optimization method and specific examples in the first embodiment are also applicable to the logistics transportation route optimization system of the present embodiment. Through the above detailed description of the logistics transportation route optimization method, those skilled in the art can clearly know the logistics transportation route optimization system of the present embodiment, so for the sake of brevity of the specification, it will not be described in detail here. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0082] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be 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 present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0083] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. A method for optimizing logistics transportation routes, characterized in that: The method comprises: Interactive logistics and transportation management system, fitting forward logistics route collection; receiving first reverse logistics information, and collecting requested logistics route information and requested logistics time information of the first reverse logistics information; Constructing a road network model according to the forward logistics route set; Inputting the requested logistics route information into the road network model for route overlap matching, and obtaining N identified transport routes whose route overlap is greater than a preset route overlap; Input the requested logistics time information into the road network model to perform time window overlap matching, and obtain M identified transport routes whose time window overlap is greater than a preset time window overlap; Establishing a bidirectional transport route optimization model, inputting the N identified transport routes and the M identified transport routes into the bidirectional transport route optimization model, and outputting a bidirectional transport route; The logistics transportation management system performs two-way logistics transportation according to the two-way transportation route; The N identified transport routes and the M identified transport routes are input into the bidirectional transport route optimization model, and the method includes: The bidirectional transport route optimization model uses the N identified transport routes and the M identified transport routes as initialization populations to generate an initial solution space set; Using the line overlap and the time window overlap as feature vectors to perform vector identification on each line in the solution space set, and outputting the identified initial solution space set; Performing feature fitness evaluation on the identified initial solution space set to obtain a fitness set; Optimization is performed in the fitness set, and a first optimized transportation route is output, and the first optimized transportation route is output as a bidirectional transportation route.

2. A method for optimizing logistics transportation routes according to claim 1, characterized in that: Before performing optimization in the fitness set, the method further includes: Determining whether the fitness set includes a solution having a fitness greater than or equal to a preset fitness; If a solution having a fitness greater than or equal to a preset fitness is not included, a cross line group is generated, wherein the cross line group is obtained by grouping two lines together; Perform crossing according to the crossing line group to generate an expanded solution space set; The initial solution space set is updated according to the expanded solution space set.

3. A method for optimizing logistics transportation routes as claimed in claim 2, characterized in that: Crossing is performed according to the cross-line group, including: Performing cross entropy identification on each group of cross-circuit lines in the cross-circuit group, and outputting cross entropy indicators corresponding to each of the cross-circuit groups; Among them, the cross entropy index is the entropy value assigned to identify the cross effect of each group of cross lines. The cross entropy identification includes identifying the line overlap complementarity and window synchronization of each group of cross lines. According to the cross entropy index, identify the cross entropy index greater than or equal to the preset cross entropy index. Cross-line groups; Based on the The cross nodes of the cross line groups are crossed to generate a cross solution space set.

4. A method for optimizing logistics transportation routes as claimed in claim 3, characterized in that: If there is no solution with a fitness greater than or equal to the preset fitness, identify a solution with a fitness less than the preset cross entropy index. A cross-line group, based on the The mutation nodes of the cross-line groups are randomly mutated to generate a set of mutation solution spaces; An expanded solution space set is generated according to the crossover solution space set and the variation solution space set.

5. A method for optimizing logistics transportation routes according to claim 1, characterized in that: Inputting the requested logistics route information into the road network model to perform route overlap matching and obtain the route overlap degree, including: Obtaining a node set and an edge set of each line in the road network model; According to the requested logistics route information, obtaining overlapping nodes and overlapping edges of each route in the node set and the edge set; The line overlap degree is obtained based on the proportion of overlapping nodes and overlapping edges of each line.

6. A method for optimizing logistics transportation routes according to claim 1, characterized in that: Get the time window overlap, the method includes: Obtaining the time window of each route in the road network model; Create a time window list to store the time window of each line of the road network model; The time window list is sorted according to the start time of each route, and the sorted time window list is scanned to obtain the overlapping window time period of the time window of each route and the time window of the requested logistics time information, and the time window overlap degree is output based on the proportion of the overlapping window time period to the total time period of the route.

7. A method for optimizing logistics transportation routes according to claim 1, characterized in that: The method further comprises: Obtaining a reverse logistics information set within a preset area, performing node frequency identification according to a bidirectional transportation route set corresponding to the reverse logistics information set, and setting a reverse transit node, wherein the reverse transit node is a route node with the largest node frequency in the bidirectional transportation route set; The logistics transportation management system uses the reverse transit node to perform transit management on the preset area.

8. A logistics transportation route optimization system, characterized in that: The system is used to implement the steps of a logistics transportation route optimization method as described in any one of claims 1 to 7, comprising: The route set acquisition module is used for interactive logistics and transportation management systems to fit forward logistics route sets; A message receiving module, used for receiving first reverse logistics information, and collecting requested logistics route information and requested logistics time information of the first reverse logistics information; A road network model building module, used to build a road network model according to the forward logistics route set; An overlapping matching module, used for inputting the requested logistics route information into the road network model for route overlapping matching, and obtaining N identified transport routes whose route overlapping degree is greater than a preset route overlapping degree; An overlap judgment module is used to input the road network model according to the requested logistics time information to perform time window overlap matching, and obtain M identified transport routes whose time window overlap is greater than a preset time window overlap; A two-way transport route output module is used to establish a two-way transport route optimization model, input the N identified transport routes and the M identified transport routes into the two-way transport route optimization model, and output a two-way transport route; The two-way transportation module, the logistics transportation management system performs two-way logistics transportation according to the two-way transportation route.

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