Logistics route data processing method and device, equipment, medium and product

Abstract

The invention relates to a data processing method, device and equipment of a logistics route, a medium and a product, and relates to the technical field of logistics of human logistics routes. The method comprises the steps of obtaining route information carried by a data processing instruction in response to the data processing instruction; the route information comprises a first route before optimization and a second route after optimization; respectively extracting a plurality of route points in the first route and the second route; connecting the plurality of route points based on the association relationship among the plurality of route points to obtain a route association graph; performing graph segmentation on the route association graph to obtain a segmentation result; and based on the segmentation result, matching the first route and the second route to obtain a route matching result. By adopting the method, the route matching efficiency can be improved.

Description

Technical Field

[0001] This application relates to the field of logistics technology, and particularly to a data processing method, device, equipment, medium and product for logistics routes. Background Art

[0002] In the logistics industry, a logistics route refers to the transportation route of a vehicle. During the actual transportation process, the route is often optimized, that is, a new route is designed. To ensure logistics efficiency, it is necessary to obtain the optimization situation in a timely manner, that is, it is necessary to know in a timely manner which old routes have been optimized and what new routes they have been optimized into.

[0003] To address this problem, currently, a route difference table is usually made manually to reflect the correlation between the routes before and after optimization. However, making a route difference table manually takes a lot of time and easily leads to low efficiency in route matching. Summary of the Invention

[0004] Based on this, to solve the above technical problems, it is necessary to provide a data processing method, device, computer equipment, computer-readable storage medium and computer program product for logistics routes that can improve the matching efficiency of logistics routes.

[0005] In a first aspect, this application provides a data processing method for logistics routes. The method includes: in response to a data processing instruction, obtaining the route information carried by the data processing instruction; the route information includes a first route before optimization and a second route after optimization; respectively extracting multiple route points from the first route and the second route; based on the correlation between the multiple route points, connecting the multiple route points to obtain a route correlation graph; performing graph segmentation on the route correlation graph to obtain a segmentation result; and based on the segmentation result, matching the first route and the second route to obtain a route matching result.

[0006] In a second aspect, this application also provides a data processing device for logistics routes. The device includes: a route obtaining module, configured to obtain the route information carried by the data processing instruction in response to the data processing instruction; the route information includes a first route before optimization and a second route after optimization; a route point extraction module, configured to respectively extract multiple route points from the first route and the second route; a correlation graph construction module, configured to connect the multiple route points based on the correlation between the multiple route points to obtain a route correlation graph; a graph segmentation module, configured to perform graph segmentation on the route correlation graph to obtain a segmentation result; and a matching module, configured to match the first route and the second route based on the segmentation result to obtain a route matching result.

[0007] In a third aspect, the present application also provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the following steps are implemented: in response to a data processing instruction, obtain the route information carried by the data processing instruction; the route information includes a first route before optimization and a second route after optimization; respectively extract a plurality of route points from the first route and the second route; based on the association relationship between the plurality of route points, connect the plurality of route points to obtain a route association graph; perform graph segmentation on the route association graph to obtain a segmentation result; based on the segmentation result, match the first route and the second route to obtain a route matching result.

[0008] In a fourth aspect, the present application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon. When the computer program is executed by a processor, the following steps are implemented: in response to a data processing instruction, obtain the route information carried by the data processing instruction; the route information includes a first route before optimization and a second route after optimization; respectively extract a plurality of route points from the first route and the second route; based on the association relationship between the plurality of route points, connect the plurality of route points to obtain a route association graph; perform graph segmentation on the route association graph to obtain a segmentation result; based on the segmentation result, match the first route and the second route to obtain a route matching result.

[0009] In a fifth aspect, the present application also provides a computer program product. The computer program product includes a computer program. When the computer program is executed by a processor, the following steps are implemented: in response to a data processing instruction, obtain the route information carried by the data processing instruction; the route information includes a first route before optimization and a second route after optimization; respectively extract a plurality of route points from the first route and the second route; based on the association relationship between the plurality of route points, connect the plurality of route points to obtain a route association graph; perform graph segmentation on the route association graph to obtain a segmentation result; based on the segmentation result, match the first route and the second route to obtain a route matching result.

[0010] The above data processing method, device, computer equipment, computer-readable storage medium and computer program product for logistics routes first respond to a data processing instruction, obtain the route information carried by the data processing instruction, including a first route before optimization and a second route after optimization, respectively extract multiple route points in the first route and the second route, and connect the multiple route points based on the association relationship between the multiple route points to obtain a route association graph. Then, perform graph segmentation on the route association graph to obtain a segmentation result. In this way, based on the segmentation result, match the first route before optimization and the second route after optimization to obtain a route matching result. The automatic matching of the routes before and after optimization is realized by using the route association graph and graph segmentation, without manually creating a route difference table, saving the route matching time, reducing the manual production error, thereby improving the matching efficiency and accuracy of the logistics route, further accelerating the iterative optimization process of the logistics route, and facilitating the implementation and application of the logistics route. Description of the Drawings

[0011] Figure 1 Schematic diagram of the application scenario of the data processing method for logistics routes in an embodiment;

[0012] Figure 2 Schematic diagram of the process of the data processing method for logistics routes in an embodiment;

[0013] Figure 3 Route association graph in an embodiment;

[0014] Figure 4 Schematic diagram of the process of generating a route association graph in an embodiment;

[0015] Figure 5 Schematic diagram of the process of graph segmentation in an embodiment;

[0016] Figure 6 Schematic diagram of graph segmentation in an embodiment;

[0017] Figure 7 Structural block diagram of the data processing device for logistics routes in an embodiment;

[0018] Figure 8 Internal structure diagram of computer equipment in an embodiment. Detailed Description of the Embodiment

[0019] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0020] In the logistics industry, a logistics route refers to the transportation route of a vehicle. During the actual transportation process, the route is often optimized, that is, a new route is designed. To ensure logistics efficiency, it is necessary to obtain the optimization situation in a timely manner, that is, it is necessary to know in a timely manner which old routes have been optimized and what new routes they have been optimized into. To address this problem, currently, a route difference table is usually manually created to reflect the correlation between the routes before and after optimization. However, manually creating a route difference table takes a lot of time and easily leads to low efficiency in route matching. Moreover, it is easy to make mistakes during the process of manually creating the route difference table, resulting in a low accuracy rate of route matching. Therefore, this application proposes a data processing method for logistics routes, which realizes the automatic matching of routes before and after optimization by establishing a route correlation graph and graph segmentation, without the need to manually create a route difference table, improving the efficiency of route matching while reducing manual errors and increasing the accuracy rate of route matching.

[0021] The data processing method for logistics routes provided by the embodiments of the present disclosure can be applied to an application environment as Figure 1 shown. It includes a server 102 and a terminal 104, and the server 102 communicates with the terminal 104. Specifically, in response to a data processing instruction sent by the terminal 104, the server 102 obtains the route information carried by the data processing instruction, that is, the first route before optimization and the second route after optimization, and respectively extracts multiple route points from the first route and the second route. Based on the correlation between the multiple route points, the multiple route points are connected to obtain a route correlation graph, and then the route correlation graph is segmented to obtain a segmentation result. Finally, based on the segmentation result, the first route and the second route are matched to obtain a route matching result. Among them, the server 102 can be implemented by an independent server or a server cluster composed of multiple servers, and the terminal 104 can be, but is not limited to, various desktop computers, laptop computers, smart phones, tablet computers, and Internet of Things devices.

[0022] In one embodiment, as Figure 2 shown, a data processing method for logistics routes is provided. Taking the method applied to the Figure 1 server 102 as an example, the method includes the following steps:

[0023] Step S202, in response to the data processing instruction, obtain the route information carried by the data processing instruction; the route information includes the first route before optimization and the second route after optimization.

[0024] Among them, the data processing instruction can be an instruction for route matching. The first route can refer to each route before route optimization, and the second route can refer to each route after route optimization. Both the first route and the second route can include a collection route and a bulk cargo route. The collection route can refer to the route from the network point to the transfer yard, and the bulk cargo route can refer to the route from the transfer yard to each network point.

[0025] Specifically, when the server receives the data processing instruction sent by the terminal, it obtains the route information carried by the data processing instruction, that is, the first route before optimization and the second route after optimization. In one example, the route information can be in the form of a route table, and all the first routes and second routes can be recorded in the route table.

[0026] Step S204: Extract multiple route points from the first route and the second route respectively.

[0027] Among them, the route points can include the starting point, ending point, and stop points of each route. There are multiple first route points corresponding to the first route, and multiple second route points corresponding to the second route.

[0028] Specifically, after the server obtains all the first routes and second routes, it can extract route points from the first route and the second route respectively, to obtain multiple first route points corresponding to the first route, and multiple second route points corresponding to the second route.

[0029] Step S206: Based on the association relationship between multiple route points, connect the multiple route points to obtain a route association graph.

[0030] Among them, the association relationship can refer to the existence relationship of each route point in the same route, and the route association graph can be a graph used to describe the association relationship between each route point.

[0031] For example, as Figure 3 shown, Figure 3 contains route A, route B, route C, route D, route E, route F, and route G. If there is an association relationship between route A and route B, then connect route A and route B. If there is an association relationship between route B and route C, then connect route B and route C. If there is an association relationship between route A and route D, then connect route A and route D. If there is an association relationship between route C and route D, then connect route C and route D. If there is an association relationship between route E and route F, then connect route E and route F. If there is an association relationship between route E and route G, then connect route E and route G. If there is an association relationship between route F and route G, then connect route F and route G. And if there is no association relationship between route E, route F, and route G and route A, route B, route C, and route D respectively, then do not connect.

[0032] Specifically, after the server obtains all the first route points corresponding to the first routes and all the second route points corresponding to the second routes, the first route points and the second route points can be merged. After the merger, according to the association relationships between the respective route points, the route points with association relationships are connected, while the route points without association relationships may not be connected. Finally, a route association graph can be obtained.

[0033] In an embodiment, based on the association relationships between multiple route points, connecting the multiple route points to obtain a route association graph further includes: obtaining a first route point set corresponding to multiple first route points and a second route point set corresponding to multiple second route points; merging and removing duplicates from the first route point set and the second route point set to obtain a target route point set; extracting multiple target route points from the target route point set, and connecting the multiple target route points to obtain a route association graph.

[0034] Among them, the first route point set may refer to the set composed of the respective route points corresponding to the first route, and the second route point set may refer to the set composed of the respective route points corresponding to the second route. The target route point set may refer to the set obtained by merging and removing duplicates from the first route point set and the second route point set, that is, the union between the first route set and the second route set. The target route point may refer to each route point in the target route point set.

[0035] For example, assume that the first route point set is {a, b}, the second route point set is {b, c, d}, then the target route point set is {a, b, c, d}, and the target route points include route point a, route point b, route point c, and route point d.

[0036] Specifically, the server can combine multiple first route points to obtain a first route point set, and combine multiple second route points to obtain a second route point set, then take the union between the first route point set and the second route point set to obtain a target route point set, and extract each target route point from the target route point set. According to the association relationships between each target route point, each target route point is connected, thereby obtaining a route association graph.

[0037] Step S208: Perform graph segmentation on the route association graph to obtain a segmentation result.

[0038] Among them, the segmentation result includes multiple common route point sets.

[0039] Specifically, by traversing the route association graph, multiple paths connected by nodes can be obtained. Based on these paths, the route association graph is segmented to obtain multiple connected components. All nodes in each connected component are connected. The route points corresponding to each node in each connected component are combined into a common route point set.

[0040] Step S210, based on the segmentation result, match the first route and the second route to obtain a route matching result.

[0041] Among them, the route matching result can be used to represent the mapping relationship between the matched first route and the second route.

[0042] Specifically, after the server obtains the segmentation result, that is, the common route point set, based on the common route point set, the first route and the second route are matched, so as to obtain the mapping relationship between the matched first route and the second route.

[0043] In one embodiment, based on the segmentation result, matching the first route and the second route to obtain a route matching result includes: traversing the first route and the second route to obtain a first route point set corresponding to the first route and a second route point set corresponding to the second route; performing route matching based on the first route point set, the second route point set, and the common route point set to obtain a route matching result.

[0044] Specifically, after the server obtains the segmentation result, that is, the common route point set, it can traverse the first route point set of each first route and the second route set of each second route, so as to match each first route and each second route based on each first route point set, each second route point set, and the common route point set, so as to obtain the matched first route and the matched second route.

[0045] In one embodiment, performing route matching based on the first route point set, the second route point set, and the common route point set to obtain a route matching result includes: performing intersection detection on the first route point set and the second route point set with the common route point set respectively to obtain an intersection detection result; if the intersection detection result indicates that both the first route point set and the second route point set have intersections with the common route point set, it is determined that the first route corresponding to the first route point set matches the second route corresponding to the second route point set, and a route matching result between the first route and the second route is generated.

[0046] Among them, the intersection detection result may include a first intersection detection result and a second intersection detection result. The first intersection detection result can be used to indicate whether there is an intersection between the first route point set and the common route point set, and the second intersection detection result can be used to indicate whether there is an intersection between the second route point set and the common route point set.

[0047] Specifically, traverse all the first route point sets, and perform intersection detection on all the first route point sets and the common route point set to obtain the first intersection detection result. Also, traverse all the second route point sets, and perform intersection detection on all the second route point sets and the common route point set to obtain the second intersection detection result. Extract the first route corresponding to the result indicating the existence of an intersection between the first route point set and the common route point set in the first intersection detection result, and the second route corresponding to the result indicating the existence of an intersection between the second route point set and the common route point set in the second intersection detection result. Since both the first route and the second route have intersections with the common route point set, it can be considered that these two routes match, thereby generating a mapping relationship between the first route and the second route.

[0048] In this embodiment, the server first responds to a data processing instruction, obtains the route information carried by the data processing instruction, including the first route before optimization and the second route after optimization, respectively extracts multiple route points from the first route and the second route, and based on the association relationship between the multiple route points, connects the multiple route points to obtain a route association graph. Then, perform graph segmentation on the route association graph to obtain a segmentation result. In this way, based on the segmentation result, match the first route before optimization and the second route after optimization to obtain a route matching result. Using the route association graph and the method of graph segmentation to achieve automatic matching of the routes before and after optimization, there is no need to manually create a route difference table, saving the route matching time and reducing manual production errors, thereby improving the matching efficiency and accuracy of the logistics route, further accelerating the iterative optimization process of the logistics route, and facilitating the implementation and application of the logistics route.

[0049] In one embodiment, as Figure 4 shown, based on the association relationship between multiple route points, connect the multiple route points to obtain a route association graph, including:

[0050] Step S402, if multiple route points exist in the same target route, determine that there is an association relationship between the multiple route points; the target route is any one of the first route or the second route.

[0051] Among them, the association relationship can refer to the existence relationship of each route point in the same target route, that is, if each route point exists in the same target route, it can be considered that there is an association relationship between each route point. The target route can be any one of the first route or any one of the second route.

[0052] Specifically, for each route point, if it coexists with other route points in any one of the first routes, or if it coexists with other route points in any one of the second routes, then an association relationship is considered to exist between this route point and the other route points.

[0053] Step S404: Connect multiple route points with an association relationship to obtain a route association graph.

[0054] Specifically, connect each route point with an association relationship, that is, connect each route point existing in the same target route. Route points without an association relationship may not be connected. Eventually, a route association graph can be obtained.

[0055] In this embodiment, establishing a route association graph based on the association relationships between each route point can improve the accuracy of the route association graph, thereby improving the accuracy of subsequent route matching.

[0056] In one embodiment, as Figure 5 shown, perform graph segmentation on the route association graph to obtain a segmentation result, including:

[0057] Step S502: Traverse the route association graph to obtain multiple target paths; a target path refers to a connected route composed of connected nodes in the route association graph.

[0058] Among them, each node in the connected route is connected. The depth-first search algorithm or the breadth-first search algorithm can be used for graph segmentation. The depth-first search algorithm (Depth-First-Search, DFS) is an algorithm based on a graph or search tree. Starting from the starting vertex, it selects a certain path to depth-first explore and find the target vertex. When the target vertex does not exist on this path, it backtracks to the starting vertex and continues to select another path to depth-first explore and find the target vertex until the target vertex is found or all vertices have been explored and then backtracks to the starting vertex to complete the search. The breadth-first search algorithm (Breadth-First-Search, BFS) is one of the simplest graph algorithms. Its feature is that when scanning the data space, each point generates a breadth-first spanning tree with the shortest path. This breadth-first search algorithm traverses all nodes of the entire graph and records them until the required result is found.

[0059] Specifically, the depth-first search algorithm or the breadth-first search algorithm can be used to traverse all nodes in the route association graph to obtain multiple connected routes composed of connected nodes.

[0060] Step S504: Based on multiple target paths, perform graph segmentation on the route association graph to obtain multiple sets of common route points.

[0061] Specifically, after multiple target paths are searched, the route association graph can be graph-segmented according to the multiple target paths, and the route points corresponding to each segmented target path can be extracted and combined into a set of common route points corresponding to each target path. In this way, multiple sets of common route points can be obtained for subsequent route matching.

[0062] For example, as Figure 6 shown, Route A, Route B, Route C, and Route D form a target path, and Route E, Route F, and Route G form a target path. Therefore, after graph segmentation, two segmented subgraphs can be obtained. The route points in each segmented subgraph are combined to obtain a set of common route points, that is, the set of common route points can be set {A, B, C, D} and set {E, F, G}.

[0063] In this embodiment, the depth-first search algorithm or the breadth-first search algorithm is used for graph traversal, so as to traverse and obtain multiple connected routes and perform graph segmentation, and then obtain multiple sets of common route points, which can improve the efficiency and accuracy of graph segmentation, thereby improving the generation efficiency and accuracy of the set of common route points, and further improving the efficiency and accuracy of subsequent route matching.

[0064] In a specific embodiment, when the server of the logistics route matching system receives a data processing instruction initiated by a user at a terminal, it first obtains the route table carried by the instruction. The route table may record all the first routes before optimization and all the second routes after optimization. For each route, route points are extracted to obtain a set of route points corresponding to each route, that is, the first set of route points corresponding to the first route and the second set of route points corresponding to the second route. Then, all the first sets of route points and all the second sets of route points are merged and de-duplicated to obtain a set of target route points. Next, for each target route point in the set of target route points, an association relationship is judged, that is, the target route points existing in the same target route are considered to have an association relationship. The target route is any one of all the first routes or any one of all the second routes. The target route points with an association relationship are connected, and the target route points without an association relationship may not be connected. Finally, a route association graph can be obtained. Then, the depth-first search algorithm or the breadth-first search algorithm is used to traverse the route association graph to obtain multiple target paths. The target path refers to a connected route composed of connected nodes in the route association graph. Based on the multiple target paths, the route association graph is graph-segmented, and the route points corresponding to each node in each of the segmented target paths are extracted. These route points are combined to obtain multiple sets of common route points. Finally, all the first sets of route points and all the second sets of route points are traversed. The first set of route points is detected for intersection with the set of common route points, that is, it is detected whether there is an intersection between the first set of route points and the set of common route points, and the second set of route points is detected for intersection with the set of common route points, that is, it is detected whether there is an intersection between the second set of route points and the set of common route points. The first route corresponding to the first set of route points and the second route corresponding to the second set of route points that have an intersection with the same set of common route points are considered to be matched, and a mapping relationship between the first route and the second route is generated.

[0065] In this embodiment, the automatic matching of the routes before and after optimization is realized by using the route association graph and graph segmentation. There is no need to manually make a route difference table, which saves the route matching time and reduces the manual production error, thereby improving the matching efficiency and accuracy of the logistics route, further accelerating the iterative optimization process of the logistics route, and facilitating the implementation and application of the logistics route.

[0066] It should be understood that although the steps in the flowcharts involved in the above embodiments are sequentially shown according to the indications of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of the steps or stages in other steps or other steps.

[0067] Based on the same inventive concept, an embodiment of the present application further provides a data processing device for a logistics route for implementing the data processing method of the logistics route involved above. The solution provided by this device for solving problems is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the data processing device for the logistics route provided below can refer to the limitations on the data processing method of the logistics route in the above text, and will not be repeated here.

[0068] In one embodiment, as Figure 7 shown, a data processing device for a logistics route is provided, including: a route acquisition module 702, a route point extraction module 704, an association graph construction module 706, a graph segmentation module 708, and a matching module 710, where: the route acquisition module 702 is configured to obtain the route information carried in the data processing instruction in response to the data processing instruction; the route information includes a first route before optimization and a second route after optimization; the route point extraction module 704 is configured to extract multiple route points from the first route and the second route respectively; the association graph construction module 706 is configured to connect the multiple route points based on the association relationship between the multiple route points to obtain a route association graph; the graph segmentation module 708 is configured to perform graph segmentation on the route association graph to obtain a segmentation result; the matching module 710 is configured to match the first route and the second route based on the segmentation result to obtain a route matching result.

[0069] In one of the embodiments, the association graph construction module 706 is further configured to: if multiple route points exist in the same target route, determine that there is an association relationship between the multiple route points; the target route is any one of the first route or the second route. Connect the multiple route points with an existing association relationship to obtain a route association graph.

[0070] In one embodiment, the graph segmentation module 708 is further configured to: traverse the route association graph to obtain a plurality of target paths; a target path refers to a connected route composed of connected nodes in the route association graph; based on the plurality of target paths, perform graph segmentation on the route association graph to obtain a plurality of sets of common route points.

[0071] In one embodiment, the matching module 710 further includes: a traversing unit configured to traverse the first route and the second route to obtain a first set of route points corresponding to the first route and a second set of route points corresponding to the second route; a matching unit configured to perform route matching based on the first set of route points, the second set of route points, and the set of common route points to obtain a route matching result.

[0072] In one embodiment, the matching unit further includes: performing intersection detection on the first set of route points and the second set of route points with the set of common route points respectively to obtain an intersection detection result; if the intersection detection result indicates that both the first set of route points and the second set of route points have intersections with the set of common route points, determine that the first route corresponding to the first set of route points matches the second route corresponding to the second set of route points, and generate a route matching result between the first route and the second route.

[0073] In one embodiment, the association graph construction module 706 is further configured to: obtain a first set of route points corresponding to a plurality of first route points and a second set of route points corresponding to a plurality of second route points; merge and deduplicate the first set of route points and the second set of route points to obtain a target set of route points; extract a plurality of target route points from the target set of route points and connect the plurality of target route points to obtain a route association graph.

[0074] Each module in the above data processing device for logistics routes can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor in the computer device in the form of hardware or be independent of the processor, or be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above respective modules.

[0075] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as Figure 8As shown. The computer device includes a processor, a memory, and a network interface connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store item recommendation data. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, it implements a data processing method for a logistics route.

[0076] Those skilled in the art can understand that Figure 8 the structure shown in is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0077] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented: in response to a data processing instruction, obtain the route information carried by the data processing instruction; the route information includes a first route before optimization and a second route after optimization; respectively extract a plurality of route points from the first route and the second route; based on the association relationship between the plurality of route points, connect the plurality of route points to obtain a route association graph; perform graph segmentation on the route association graph to obtain a segmentation result; based on the segmentation result, match the first route and the second route to obtain a route matching result.

[0078] In one embodiment, when the processor executes the computer program, the following steps are further implemented: if a plurality of route points exist in the same target route, it is determined that there is an association relationship between the plurality of route points; the target route is any one of the first route or the second route. Connect the plurality of route points with an existing association relationship to obtain a route association graph.

[0079] In one embodiment, when the processor executes the computer program, the following steps are further implemented: traverse the route association graph to obtain a plurality of target paths; the target path refers to a connected route composed of connected nodes in the route association graph; based on the plurality of target paths, perform graph segmentation on the route association graph to obtain a plurality of sets of common route points.

[0080] In one embodiment, when the processor executes the computer program, the following steps are further implemented: traversing the first route and the second route to obtain a first set of route points corresponding to the first route and a second set of route points corresponding to the second route; and performing route matching based on the first set of route points, the second set of route points, and the set of common route points to obtain a route matching result.

[0081] In one embodiment, when the processor executes the computer program, the following steps are further implemented: performing intersection detection on the first set of route points and the second set of route points with the set of common route points respectively to obtain an intersection detection result; if the intersection detection result indicates that both the first set of route points and the second set of route points have intersections with the set of common route points, determining that the first route corresponding to the first set of route points matches the second route corresponding to the second set of route points, and generating a route matching result between the first route and the second route.

[0082] In one embodiment, when the processor executes the computer program, the following steps are further implemented: obtaining a first set of route points corresponding to a plurality of first route points and a second set of route points corresponding to a plurality of second route points; merging and removing duplicates from the first set of route points and the second set of route points to obtain a target set of route points; extracting a plurality of target route points from the target set of route points and connecting the plurality of target route points to obtain a route association graph.

[0083] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: in response to a data processing instruction, obtaining route information carried by the data processing instruction; the route information includes a first route before optimization and a second route after optimization; respectively extracting a plurality of route points from the first route and the second route; connecting the plurality of route points based on the association relationship between the plurality of route points to obtain a route association graph; performing graph segmentation on the route association graph to obtain a segmentation result; and performing matching on the first route and the second route based on the segmentation result to obtain a route matching result.

[0084] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: if a plurality of route points exist in the same target route, determining that there is an association relationship between the plurality of route points; the target route is any one of the first route or the second route. Connecting the plurality of route points having an association relationship to obtain a route association graph.

[0085] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: traversing the route association graph to obtain a plurality of target paths; the target path refers to a connected route composed of connected nodes in the route association graph; and performing graph segmentation on the route association graph based on the plurality of target paths to obtain a plurality of sets of common route points.

[0086] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: traversing the first route and the second route to obtain a set of first route points corresponding to the first route and a set of second route points corresponding to the second route; and performing route matching based on the set of first route points, the set of second route points, and the set of common route points to obtain a route matching result.

[0087] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: performing intersection detection on the set of first route points and the set of second route points respectively with the set of common route points to obtain an intersection detection result; if the intersection detection result indicates that both the set of first route points and the set of second route points have intersections with the set of common route points, determining that the first route corresponding to the set of first route points matches the second route corresponding to the set of second route points, and generating a route matching result between the first route and the second route.

[0088] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: obtaining a set of first route points corresponding to a plurality of first route points and a set of second route points corresponding to a plurality of second route points; merging and de-duplicating the set of first route points and the set of second route points to obtain a set of target route points; extracting a plurality of target route points from the set of target route points and connecting the plurality of target route points to obtain a route association graph.

[0089] In one embodiment, a computer program product is provided, including a computer program, which when executed by a processor, implements the following steps: in response to a data processing instruction, obtaining the route information carried by the data processing instruction; the route information includes a first route before optimization and a second route after optimization; respectively extracting a plurality of route points from the first route and the second route; connecting the plurality of route points based on the association relationship between the plurality of route points to obtain a route association graph; performing graph segmentation on the route association graph to obtain a segmentation result; and performing matching on the first route and the second route based on the segmentation result to obtain a route matching result.

[0090] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: if a plurality of route points exist in the same target route, determining that there is an association relationship between the plurality of route points; the target route is any one of the first route or the second route. Connecting the plurality of route points having an association relationship to obtain a route association graph.

[0091] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: traversing the route association graph to obtain a plurality of target paths; the target path refers to a connected route composed of connected nodes in the route association graph; and performing graph segmentation on the route association graph based on the plurality of target paths to obtain a plurality of sets of common route points.

[0092] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: traversing the first route and the second route to obtain a set of first route points corresponding to the first route and a set of second route points corresponding to the second route; performing route matching based on the set of first route points, the set of second route points, and the set of common route points to obtain a route matching result.

[0093] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: performing intersection detection on the set of first route points and the set of second route points with the set of common route points respectively to obtain an intersection detection result; if the intersection detection result indicates that both the set of first route points and the set of second route points have intersections with the set of common route points, determining that the first route corresponding to the set of first route points matches the second route corresponding to the set of second route points, and generating a route matching result between the first route and the second route.

[0094] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: obtaining a set of first route points corresponding to a plurality of first route points and a set of second route points corresponding to a plurality of second route points; merging and de-duplicating the set of first route points and the set of second route points to obtain a set of target route points; extracting a plurality of target route points from the set of target route points and connecting the plurality of target route points to obtain a route association graph.

[0095] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0096] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logics, data processing logics based on quantum computing, etc., without limitation.

[0097] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0098] The above embodiments only represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A data processing method for a logistics route, characterized in that, The method includes: In response to a data processing instruction, obtaining the route information carried by the data processing instruction; the route information includes a first route before optimization and a second route after optimization; Respectively extracting a plurality of route points from the first route and the second route; Based on the association relationship between the plurality of route points, connecting the plurality of route points to obtain a route association graph; Performing graph segmentation on the route association graph to obtain a segmentation result; Based on the segmentation result, matching the first route and the second route to obtain a route matching result.

2. The method according to claim 1, characterized in that, The step of based on the association relationship between the plurality of route points, connecting the plurality of route points to obtain a route association graph includes: If the plurality of route points exist in the same target route, it is determined that there is an association relationship between the plurality of route points; the target route is any one of the first route or the second route. Connecting the plurality of route points with an association relationship to obtain the route association graph.

3. The method according to claim 1, wherein The segmentation result includes a plurality of common route point sets. The step of performing graph segmentation on the route association graph to obtain a segmentation result includes: Traversing the route association graph to obtain a plurality of target paths; the target path refers to a connected route composed of connected nodes in the route association graph; Based on the plurality of target paths, performing graph segmentation on the route association graph to obtain the plurality of common route point sets.

4. The method according to claim 1, characterized in that, The segmentation result includes a plurality of common route point sets. The step of based on the segmentation result, matching the first route and the second route to obtain a route matching result includes: Traversing the first route and the second route to obtain a first route point set corresponding to the first route and a second route point set corresponding to the second route; Based on the first route point set, the second route point set and the common route point set, performing route matching to obtain the route matching result.

5. The method according to claim 4, characterized in that, The step of based on the first route point set, the second route point set and the common route point set, performing route matching to obtain the route matching result includes: Performing intersection detection on the first route point set and the second route point set respectively with the common route point set to obtain an intersection detection result; If the intersection detection result indicates that both the first route point set and the second route point set have an intersection with the common route point set, it is determined that the first route corresponding to the first route point set matches the second route corresponding to the second route point set, and a route matching result between the first route and the second route is generated.

6. The method according to claim 1, characterized in that The route points include first route points corresponding to the first route and second route points corresponding to the second route. The step of based on the association relationship between the plurality of route points, connecting the plurality of route points to obtain a route association graph further includes: Obtaining a first route point set corresponding to the plurality of first route points and a second route point set corresponding to the plurality of second route points; Merging and de-duplicating the first route point set and the second route point set to obtain a target route point set; Extract multiple target route points from the set of target route points, and connect the multiple target route points to obtain the route association graph.

7. A data processing device for a logistics route, characterized in that, The device includes: A route acquisition module, configured to acquire the route information carried by the data processing instruction in response to the data processing instruction; the route information includes a first route before optimization and a second route after optimization; A route point extraction module, configured to extract multiple route points from the first route and the second route respectively; An association graph construction module, configured to connect the multiple route points based on the association relationship between the multiple route points to obtain a route association graph; A graph segmentation module, configured to perform graph segmentation on the route association graph to obtain a segmentation result; A matching module, configured to match the first route and the second route based on the segmentation result to obtain a route matching result.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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