Logistics transportation method and device, computer device and storage medium

Abstract

The application provides a logistics transportation method and device, computer equipment and a storage medium, comprising: obtaining order information and position information of a node to be planned; based on a preset three-dimensional loading algorithm containing a three-dimensional loading constraint, analyzing the order information and the position information to obtain an initial logistics line meeting the three-dimensional loading constraint; based on the number of nodes contained in each initial logistics line, optimizing the initial logistics line to obtain a target logistics line for logistics transportation. The method can plan a reasonable line and loading scheme for a logistics transportation task, can not only meet the timeliness of the logistics transportation task, but also improve the loading rate of the logistics transportation task, avoid the problem of suspended or overloaded goods of the logistics transportation vehicle, save the logistics transportation cost, and improve the logistics transportation efficiency.

Description

Technical Field

[0001] This application relates to the field of logistics technology, specifically to a logistics transportation method, apparatus, computer equipment, and storage medium. Background Technology

[0002] Currently, the selection of logistics transportation routes is mainly based on driver experience, lacking comprehensive consideration of transportation costs and timeliness, as well as scientific loading operation guidelines, leading to varying degrees of space waste. Therefore, a route planning and loading scheme that is easy to implement and has a high loading rate is needed as an operational guide to promote the rationalization of both route selection and loading.

[0003] However, existing route planning methods do not take into account other logistics factors, such as the cargo loading tasks that need to be completed during the implementation of each route. This inevitably leads to problems such as cargo being suspended or overloaded when logistics transportation is carried out according to the route.

[0004] Therefore, existing route planning methods suffer from technical problems such as low logistics and transportation efficiency due to unreasonable route planning. Summary of the Invention

[0005] Therefore, it is necessary to provide a logistics transportation method, device, computer equipment, and storage medium to address the aforementioned technical problems, so as to rationally plan the transportation routes and loading schemes for logistics distribution tasks, reduce the risk of errors, and thereby improve logistics transportation efficiency.

[0006] In a first aspect, this application provides a logistics transportation method, including:

[0007] Obtain order and location information for the nodes to be planned;

[0008] Based on a preset 3D loading algorithm that includes 3D loading constraints, order information and location information are analyzed to obtain an initial logistics route that satisfies the 3D loading constraints.

[0009] Based on the number of nodes included in each initial logistics route, the initial logistics routes are optimized to obtain the target logistics routes for logistics transportation.

[0010] In some embodiments of this application, based on a preset three-dimensional loading algorithm containing three-dimensional loading constraints, order information and location information are analyzed to obtain an initial logistics route that satisfies the three-dimensional loading constraints. This includes: when the node to be planned is not empty, obtaining vehicle working time and vehicle capacity information corresponding to the currently available route; based on the preset three-dimensional loading algorithm containing three-dimensional loading constraints, analyzing order information, location information, vehicle working time and / or vehicle capacity information to obtain analysis results; and based on the analysis results, selecting target routes from the currently available routes as the initial logistics route.

[0011] In some embodiments of this application, based on a preset 3D loading algorithm including 3D loading constraints, order information, location information, vehicle working time and / or vehicle capacity information are analyzed to obtain analysis results. This includes: determining an objective function for planning a logistics route, where the objective function is a first objective function and / or a second objective function; if the objective function is a first objective function and a second objective function, then according to the preset priority of each objective function, the route planning information is analyzed in combination with the objective function and objective constraints, and the vehicle working time and / or vehicle capacity information is analyzed to obtain analysis results; wherein, the route planning information includes order information and location information; if the objective function is a first objective function or a second objective function, then the route planning information is analyzed in combination with the objective function and objective constraints, and the vehicle working time and / or vehicle capacity information is analyzed to obtain analysis results; wherein, the objective constraints include 3D loading constraints, as well as preset time window constraints and / or capacity constraints.

[0012] In some embodiments of this application, the objective function further includes a third objective function. The order information includes cargo parameter information and logistics timeliness. The route planning information is analyzed in conjunction with the objective function and objective constraints, and the vehicle working time and / or vehicle capacity information are analyzed to obtain the analysis result, including: analyzing the route planning information in conjunction with the objective function and objective constraints, and analyzing the vehicle working time and / or vehicle capacity information to obtain the cargo loading planning result; if the cargo loading planning result satisfies the objective function and objective constraints, the analysis result is determined as the first analysis result; if the cargo loading planning result does not satisfy the objective function or objective constraints, the initialized empty route is obtained, and when the logistics cost value of the node to be planned in the empty route does not meet the preset cost condition, the analysis result is determined as the second analysis result.

[0013] In some embodiments of this application, based on the analysis results, a target route is selected from the currently available routes as an initial logistics route, including: if the analysis result is a first analysis result, then the corresponding currently available route is selected as the target route; the route code of the target route is obtained; and based on the route code, the target route is selected from the currently available routes as the initial logistics route.

[0014] In some embodiments of this application, the initial logistics routes are optimized based on the number of nodes contained in each initial logistics route to obtain a target logistics route for logistics transportation. This includes: obtaining the number of nodes contained in each initial logistics route; determining the routes to be deleted in each initial logistics route based on the number of nodes, wherein the number of nodes in the routes to be deleted is the minimum value among the number of nodes; if the routes to be deleted contain nodes to be planned, then obtaining a set of routes that do not contain the routes to be deleted, and optimizing the initial logistics routes based on the set of routes to obtain a target logistics route for logistics transportation.

[0015] In some embodiments of this application, the steps of obtaining order information and location information of a node to be planned include: obtaining pickup plan information or delivery plan information of the node to be planned, wherein the pickup plan information or delivery plan information includes cargo parameter information and logistics timeliness; processing the information format of the pickup plan information or delivery plan information to obtain order information of the node to be planned; and obtaining the cargo transportation address in the pickup plan information or delivery plan information to obtain location information of the node to be planned.

[0016] Secondly, this application provides a logistics transportation device, comprising:

[0017] The information acquisition module is used to acquire order information and location information of the nodes to be planned;

[0018] The route planning module is used to analyze order information and location information based on a preset 3D loading algorithm that includes 3D loading constraints, and obtain an initial logistics route that satisfies the 3D loading constraints.

[0019] The route optimization module is used to optimize the initial logistics routes based on the number of nodes contained in each initial logistics route, so as to obtain the target logistics route for logistics transportation.

[0020] Thirdly, this application also provides a computer device, comprising:

[0021] One or more processors;

[0022] The memory; and one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the logistics transportation method.

[0023] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, the computer program being loaded by a processor to perform the steps in the logistics transportation method.

[0024] Fifthly, embodiments of this application provide a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method provided in the first aspect described above.

[0025] The aforementioned logistics transportation method, apparatus, computer equipment, and storage medium, wherein the server acquires order and location information of nodes to be planned, and analyzes the order and location information based on a preset 3D loading algorithm containing 3D loading constraints, to obtain an initial logistics route that satisfies the 3D loading constraints. Then, based on the number of nodes included in each initial logistics route, the initial logistics route is optimized to obtain the target logistics route for logistics transportation. Because this application uses a loading algorithm that dynamically generates placement points to treat 3D loading constraints as a hard condition for route planning during the logistics transportation process, it can effectively avoid situations where loading is impossible during actual route implementation. Therefore, using this method to plan reasonable routes for logistics transportation tasks avoids problems such as cargo being suspended or overloaded in logistics transportation vehicles, saving logistics transportation costs and improving logistics transportation efficiency. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a schematic diagram of a logistics transportation method in an embodiment of this application;

[0028] Figure 2 This is a flowchart illustrating the logistics transportation method in an embodiment of this application;

[0029] Figure 3 This is a schematic diagram of the algorithm framework of the logistics transportation method in the embodiments of this application;

[0030] Figure 4 This is a schematic diagram of the loading algorithm for the logistics transportation method in the embodiments of this application;

[0031] Figure 5 This is a flowchart illustrating the initial logistics route acquisition step in an embodiment of this application;

[0032] Figure 6 This is a flowchart illustrating the initial logistics route optimization steps in an embodiment of this application;

[0033] Figure 7 This is a schematic diagram of the structure of the logistics transportation device in the embodiments of this application;

[0034] Figure 8 This is a schematic diagram of the structure of the computer device in the embodiments of this application. Detailed Implementation

[0035] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0036] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0037] In the description of this application, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0038] This application provides a logistics transportation method, apparatus, computer equipment, and storage medium, which will be described in detail below.

[0039] See Figure 1 , Figure 1This is a schematic diagram illustrating a scenario of the logistics transportation method provided in this application, which can be applied to a logistics transportation system. The logistics transportation system includes a terminal 100 and a server 200 connected via a network. The terminal 100 can be a device that includes both receiving and transmitting hardware, i.e., a device with receiving and transmitting hardware capable of performing bidirectional communication over a bidirectional communication link. Such a device can include cellular or other communication devices, having a single-line display, a multi-line display, or a cellular or other communication device without a multi-line display. Specifically, the terminal 100 can be a desktop terminal or a mobile terminal, and can also be a mobile phone, tablet computer, laptop computer, etc. The server 200 can be a standalone server, or a server network or server cluster, including but not limited to computers, network hosts, a single network server, multiple network server sets, or a cloud server composed of multiple servers. The cloud server consists of a large number of computers or network servers based on cloud computing. The networks mentioned in this application include, but are not limited to, wide area networks (WANs), metropolitan area networks (MANs), or local area networks (LANs).

[0040] Those skilled in the art will understand that Figure 1 The application environment shown is merely one applicable scenario for the solution in this application and does not constitute a limitation on the application scenario of the solution in this application. Other application environments may include more than one. Figure 1 The number of computer devices shown is more or less, for example Figure 1 Only one server 200 is shown in the diagram. It is understood that the logistics and transportation system may also include one or more other servers, which are not specified here. In addition, the logistics and transportation system may also include a storage device for storing data, such as pickup plan information, delivery plan information, etc.

[0041] It should be noted that, Figure 1 The schematic diagram of the logistics transportation system shown is merely an example. The logistics transportation system and scenario described in the embodiments of the present invention are for the purpose of more clearly illustrating the technical solutions of the embodiments of the present invention, and do not constitute a limitation on the technical solutions provided by the embodiments of the present invention. As those skilled in the art will know, with the evolution of logistics transportation systems and the emergence of new business scenarios, the technical solutions provided by the embodiments of the present invention are also applicable to similar technical problems.

[0042] See Figure 2 This application provides a logistics transportation method, mainly applied to the above. Figure 1 Taking server 200 as an example, the method includes steps S201 to S203, as follows:

[0043] S201, obtain the order information and location information of the node to be planned.

[0044] The nodes to be planned can refer to customer nodes that are not yet served and for which logistics transportation routes need to be planned, or supplier nodes that have sales needs for goods and for which logistics transportation routes need to be planned. It should be noted that when a customer is a node to be planned, the logistics transportation method provided in this application is applicable to delivery scenarios, i.e., it requires planning a delivery logistics route from the supplier to the customer; when a supplier is a node to be planned, the logistics transportation method provided in this application is applicable to pickup scenarios, i.e., it requires planning a pickup logistics route from the manufacturer to the supplier.

[0045] The order information can be in the form of an order, containing cargo parameter information and logistics time. The cargo parameter information can be cargo size information and / or cargo weight information. The logistics time can be the time when the vehicle is allowed to arrive at the planned node. For example, the logistics time is from 12:00 on January 1, 2021 to 12:00 on January 5, 2021. Another example is cargo size information as XX length XX width XX height and cargo weight information as XX kilograms (kg) or XX grams (g).

[0046] The location information can refer to the GPS location of the node to be planned, or it can refer to the legally registered location of the node to be planned, such as No. XX, XX Street, XX District, XX City.

[0047] Specifically, before analyzing logistics transportation routes for nodes to be planned, server 200 first needs to determine which nodes are to be planned, and then obtain the order information and location information of the corresponding nodes to be planned as the basis for logistics route planning analysis. Therefore, server 200 can receive instructions from terminal 100 to determine nodes to be planned (such as nodes newly submitted by terminal 100), or determine nodes to be planned by filtering a preset number of nodes based on a locally stored node list (such as filtering a certain number of nodes in order, or filtering a certain number of nodes by referring to special parameters, which can be service identifiers (identifier 0 indicates "not serviced", identifier 1 indicates "serviced", and "serviced" means that the corresponding node has been arranged in the corresponding logistics route)).

[0048] More specifically, after server 200 identifies the node to be planned, it can further obtain the order information and location information of the node to be planned. The information can be obtained in one of the following ways:

[0049] (1) Obtain the order information and location information of the nodes to be planned from the terminal 100 or other devices. That is, the various business transactions between each node to be planned and the logistics company will be edited and submitted at the terminal 100. While the terminal 100 uploads the business transaction data, it will also record the logistics business information of the account to be identified.

[0050] (2) Obtained synchronously from other servers, that is, multiple servers and / or terminals of logistics enterprises can be used as blockchain nodes to form a blockchain system, such as a public blockchain system or a private blockchain system. Although the basic attributes of these two blockchain systems are different (the information stored in the public blockchain cannot be tampered with, while the information stored in the private blockchain can be tampered with), what they have in common is that the order information and location information stored at any node server can be requested and obtained by other node servers in the system.

[0051] (3) Obtained by requesting from the superior server or by polling from the subordinate server. That is, there is a superior-subordinate relationship between multiple servers of a logistics company. After the superior server updates the data, the subordinate server can request to obtain it in real time. After the subordinate server updates the data, the superior server can poll to obtain it at regular intervals.

[0052] It is understood that the selection of the aforementioned public blockchain system, private blockchain system, request acquisition method, or polling acquisition method can be determined based on actual application needs, and this application embodiment does not impose specific limitations. The steps for obtaining order information and location information involved in this embodiment will be described in detail below.

[0053] In one embodiment, this step includes: obtaining pickup plan information or delivery plan information of the node to be planned; processing the information format of the pickup plan information or delivery plan information to obtain the order information of the node to be planned; obtaining the cargo transportation address in the pickup plan information or delivery plan information to obtain the location information of the node to be planned.

[0054] The pickup plan information refers to the pickup plans between various manufacturers and various suppliers. The pickup plan information can be obtained by analyzing the material requirements plan of each manufacturer, that is, the pickup plan of manufacturer A to various suppliers can be derived from the material requirements plan of manufacturer A.

[0055] The delivery plan information refers to the delivery plans between each supplier and each customer. The delivery plan information can be obtained by analyzing the goods demand plans of each customer. That is, the delivery plans of each supplier to customer B can be derived from customer B's goods demand plan.

[0056] The pickup or delivery plan information includes cargo parameter information and logistics time. The cargo parameter information may include cargo size information and cargo weight information, and the logistics time may refer to the time when the vehicle is allowed to arrive at the planned node.

[0057] Specifically, after identifying the node to be planned, if the node is a customer node, the server 200 can further obtain the pickup plan information of the node; if the node is a supplier node, the server 200 can further obtain the delivery plan information of the node. Then, it processes the format of the pickup or delivery plan information, such as converting the format of the stored file (e.g., converting it to Excel format), to obtain the subsequent order information. If the node is a customer node, vehicles configured for the corresponding logistics route need to travel to each customer node to unload goods; if the node is a supplier node, vehicles configured for the corresponding logistics route need to travel to each supplier node to load goods. Therefore, customers and suppliers are nodes in different scenarios.

[0058] More specifically, after obtaining the order information of the node to be planned, the server 200 can further obtain the cargo transportation address of the node to be planned, such as the enterprise registration address, order submission address, and actual location (GPS) address of the node to be planned, and then obtain the location information required for subsequent operations.

[0059] S202, based on a preset three-dimensional loading algorithm that includes three-dimensional loading constraints, analyzes order information and location information to obtain an initial logistics route that satisfies the three-dimensional loading constraints.

[0060] The three-dimensional loading constraints are based on the consideration of priority vehicle loading rate. That is, when loading goods on the current route, the specific length, width, height, and other business attributes of the goods are taken into account. The reason is that considering three-dimensional loading constraints during route planning can effectively avoid situations where loading is not possible during actual route implementation, more closely reflecting the actual logistics and transportation situation, thereby improving logistics and transportation efficiency.

[0061] Specifically, the basis for server 200's analysis and planning of logistics routes is that the node to be planned is not empty; if it is empty, there is no need to plan a logistics route. Therefore, this embodiment proposes that, when the node to be planned is not empty, a preset 3D loading algorithm containing 3D loading constraints can be used as an analysis strategy to analyze the order information and location information of the node to be planned, and filter initial logistics routes that satisfy the 3D loading constraints as selectable logistics routes for insertion into the node to be planned. The initial logistics route acquisition steps involved in this embodiment will be described in detail below.

[0062] In one embodiment, this step includes: when the node to be planned is not empty, obtaining the vehicle working time and vehicle capacity information corresponding to the currently available route; analyzing the order information, location information, vehicle working time and / or vehicle capacity information based on a preset three-dimensional loading algorithm containing three-dimensional loading constraints, and obtaining the analysis results; and selecting the target route from the currently available routes based on the analysis results as the initial logistics route.

[0063] The currently available lines can refer to lines that have been initialized and are about to be inserted into node analysis. For example, line A ("0->1->0") can also be used to insert other nodes as currently available lines. Here, "0" can represent a warehouse node and "1" can represent a customer node.

[0064] Among them, vehicle working time can refer to the working time of the corresponding vehicle configured for the currently available route. For example, the vehicle working time is from 12:00 on February 1, 2021 to 12:00 on February 3, 2021, which means that the vehicles on the currently available route are in transport operation during this period.

[0065] Among them, vehicle capacity information can refer to the cargo capacity of the corresponding vehicle configured for the currently available line. For example, vehicle capacity information of "1 ton" means that the vehicle can carry cargo with a weight of less than or equal to "1 ton"; another example is vehicle capacity information of "50 cubic meters", which means that the vehicle can carry cargo with a volume of less than or equal to "50 cubic meters".

[0066] Specifically, server 200, upon detecting that the node to be planned is not empty, first obtains the currently available lines, and then obtains the vehicle operating time and vehicle capacity information corresponding to the currently available lines. For example, Figure 3 As shown, if the node to be planned is a customer node, the node to be planned can be stored in a pre-set "customer pool", the currently available routes can be stored in a pre-set "path pool", and the pre-set "selection pool" can store the initial logistics routes corresponding to the node to be planned.

[0067] More specifically, after obtaining the vehicle working time and vehicle capacity information corresponding to each currently available route, the server 200 can analyze the order information and location information of the node to be planned based on a preset three-dimensional loading algorithm containing three-dimensional loading constraints, and analyze the vehicle working time and / or vehicle capacity information corresponding to each currently available route to obtain the analysis results, that is, to analyze whether the node to be planned can be inserted into the corresponding currently available route, and thus obtain the analysis results of whether it can be inserted or not.

[0068] Furthermore, whether to analyze vehicle operation information and vehicle capacity information depends on whether the target constraints currently configured on server 200 include time window constraints and capacity constraints. The vehicle operation information is used by server 200 to detect time window constraints, and the vehicle capacity information is used by server 200 to detect capacity constraints. Server 200 comprehensively analyzes order information, location information, and vehicle operation time, or analyzes order information, location information, and vehicle capacity information, or analyzes order information, location information, vehicle operation information, and vehicle capacity information. After obtaining the analysis results, it can filter out the target routes from the currently available routes as the initial logistics routes for the corresponding planned nodes. The objective function and constraints used in this embodiment will be described in detail below.

[0069] In one embodiment, based on a preset 3D loading algorithm including 3D loading constraints, order information, location information, vehicle working time and / or vehicle capacity information are analyzed to obtain analysis results. This includes: determining an objective function for planning the logistics route, where the objective function is a first objective function and / or a second objective function; if the objective function is the first objective function and the second objective function, then according to the preset priority of each objective function, the route planning information is analyzed in combination with the objective function and objective constraints, and the vehicle working time and / or vehicle capacity information is analyzed to obtain analysis results; wherein, the route planning information includes order information and location information; if the objective function is the first objective function or the second objective function, then the route planning information is analyzed in combination with the objective function and objective constraints, and the vehicle working time and / or vehicle capacity information is analyzed to obtain analysis results; wherein, the objective constraints include 3D loading constraints, as well as preset time window constraints and / or capacity constraints.

[0070] The objective function can refer to the functional relationship between the target (a variable) and related factors (variables). In this application, the objective functions involved include "minimum number of vehicle resources" and "shortest total driving distance".

[0071] In analyzing certain specific logic functions, we often encounter a situation where the values ​​of input variables are not arbitrary. Therefore, the restrictions imposed on the values ​​of input variables are called constraints. The constraints involved in the embodiments of this application include "time window constraints", "capacity constraints" and "three-dimensional loading constraints". When actually determining the target constraints, rich search targets can be added according to different business scenarios and business measurement indicators to achieve search optimization of multiple business targets. Under different target priorities, specific route planning and loading schemes are output.

[0072] Specifically, the objective functions used in this application embodiment include a first objective function and / or a second objective function. The first objective function is used to minimize the number of vehicle resources in the initial logistics route, and the second objective function is used to minimize the mileage of the initial logistics route. If multi-objective analysis is used, since the first objective function has a higher priority than the second objective function, it is necessary to first determine the number of vehicles used in the current solution. If the number of vehicles is the same, then the total mileage is determined. Here, the number of vehicles is the number of routes in the current solution (initial logistics route). The second objective function is expressed as: i represents node i, j represents node j, k represents line, and x ijk Indicates whether line k traverses edges ij, d ij This represents the distance between node i and node j.

[0073] More specifically, the constraints that can be selected in the embodiments of this application include time window constraints, capacity constraints, and three-dimensional loading constraints. The time window constraint limits the time available for a route to access a customer node to be within the customer-allowed time window. The capacity constraint limits the total demand for accessing customer nodes via available routes to not exceed the maximum capacity of a specified vehicle type, measured in volume or weight. The three-dimensional loading constraint limits the length, width, and height of the goods to be loaded to be considered when loading goods onto available routes. The embodiments of this application propose considering three-dimensional loading constraints during route planning, which can effectively avoid situations where loading is impossible during actual route implementation, thereby improving logistics and transportation efficiency.

[0074] Furthermore, the time window constraint is a fundamental constraint in path planning, and can be used [e i ,l i ] represents the time window of node i, e i Indicates the earliest start time of node i, l i Indicates the latest start time of accessing node i, a i Indicates the time when the vehicle arrives at node i (a i =a j +t ji +s i ), s i t represents the loading and unloading time of node i. ji Let a represent the travel time from node j to node i. Then, only if a i In the interval [e i ,l i Only when the time window constraint is met can it be determined that the solution for the corresponding line satisfies the time window constraint.

[0075] Furthermore, the capacity constraint can be expressed by the formula Q1 + Q2 + Q. n =d i ≤V represents the initial capacity. Where Q represents the initial capacity, and d...i V represents the quantity of goods picked up (taken from order information), and V represents the current capacity of the vehicle (taken from vehicle capacity information).

[0076] Furthermore, the three-dimensional loading constraint does not have a specific formula in this embodiment of the application, but the role of the three-dimensional loading constraint is to control the vehicles configured corresponding to the initial logistics route to be able to carry the cargo parameter information required by the planned node, that is, to meet the requirements in terms of weight or volume.

[0077] For example, see Figure 4 Server 200 can use the three-dimensional loading algorithm (hereinafter referred to as loading algorithm) to detect three-dimensional loading constraints, that is, follow the following rules to determine the analysis results: (1) Maximum base area priority, that is, when placing goods, the goods with the largest base area are selected first, and so on; (2) From head to tail, from inside to outside, from bottom to top, that is, when loading, the order of placing goods is from the front of the vehicle to the rear, from the inside to the outside, and from bottom to top.

[0078] Finally, if the server 200 analysis determines that the route planning information (including order information and location information), vehicle working time and / or vehicle capacity information all satisfy one or more preset objective functions and one or more preset constraints, then the analysis result for the corresponding route can be determined as the first analysis result; otherwise, it is the second analysis result. It should be noted that the first analysis result includes the loading plan, specifically the placement and arrangement of each cargo code in the corresponding logistics transport vehicle. The cargo codes and the loading volume information of the corresponding logistics transport vehicles are both present in the order information. The placement effect can be found in the [reference needed]. Figure 4 .

[0079] In one embodiment, the objective function further includes a third objective function. The order information includes cargo parameter information and logistics timeliness. The route planning information is analyzed in conjunction with the objective function and objective constraints, and the vehicle working time and / or vehicle capacity information are analyzed to obtain the analysis result, including: analyzing the route planning information in conjunction with the objective function and objective constraints, and analyzing the vehicle working time and / or vehicle capacity information to obtain the cargo loading planning result; if the cargo loading planning result satisfies the objective function and objective constraints, the analysis result is determined as the first analysis result; if the cargo loading planning result does not satisfy the objective function or objective constraints, the initialized empty route is obtained, and when the logistics cost value of the node to be planned in the empty route does not meet the preset cost condition, the analysis result is determined as the second analysis result.

[0080] The third objective function is used to maximize the vehicle loading capacity. The cargo parameter information can include cargo size information and cargo weight information. The logistics timeliness can refer to the time when the vehicle is allowed to arrive at the planned node, as explained above, so it will not be repeated in this embodiment.

[0081] Specifically, server 200 can combine the above-mentioned "customer pool", "path pool" and "selection pool" to obtain the analysis results, that is, to obtain whether the currently available lines containing nodes to be planned can be added to the selection pool. The analysis steps include: (1) initializing the "customer pool" and adding all unserved customer nodes (if it is a pickup scenario, add unserved supplier nodes); (2) if the "customer pool" is not empty, proceed to step 3, otherwise proceed to step 5; (3) determine whether the "selection pool" is empty. If it is not empty, select the optimal insertion operation from the "selection pool". The selection criteria are based on the objective function and constraints mentioned above. The customer node is inserted into the corresponding currently available path to obtain the initial logistics route of the customer node being analyzed, and then the customer node is deleted from the "customer pool"; (4) If the "selection pool" is empty, an empty path is initialized and stored in the "path pool", and the customer node in the "customer pool" is inserted into the newly opened empty path. All feasible insertion positions and insertion costs are recorded. The calculation logic of the insertion cost is determined according to the objective function and constraints. Finally, all feasible insertion selections are stored in the "selection pool" and the process returns to step 2; (5) The path in the "selection pool" is determined as the initial logistics route of the corresponding inserted node to be planned.

[0082] More specifically, the above-described selection of the optimal insertion operation from the "selection pool" uses the order and location information of the node to be planned, as well as the vehicle working time and / or vehicle capacity information of the currently available routes, as reference objects. The resulting cargo loading planning result has two possibilities: it satisfies the objective function and objective constraints, or it does not. If the analysis determines that the node to be planned, A1, does not match the currently available route, B1, further analysis is needed to determine whether the cost of the node to be planned, A1, in an empty route meets the conditions, such as being less than or equal to a certain threshold. If it still does not, then the analysis result can be determined as the second analysis result, meaning that the currently available route, B1, is not the initial logistics route for the node to be planned, A1. Conversely, the analysis result can be determined as the first analysis result, meaning that the currently available route, B1, is the initial logistics route for the node to be planned, A1.

[0083] In one embodiment, the step of selecting a target route from the currently available routes as an initial logistics route based on the analysis results includes: if the analysis result is a first analysis result, then the corresponding currently available route is selected as the target route; obtaining the route code of the target route; and selecting the target route from the currently available routes as the initial logistics route based on the route code.

[0084] The route code can refer to the identification code of each logistics route, which can be composed of numbers, letters or special characters, such as 123a, 234b, etc.

[0085] Specifically, server 200 analyzes each currently available route for the node to be planned. After obtaining the corresponding analysis results, the currently available route corresponding to the first analysis result can be used as the target route. The route code of the target route is obtained by looking up the table, thereby filtering out the target route among the currently available routes as the initial logistics route corresponding to the node to be planned.

[0086] S203, based on the number of nodes contained in each initial logistics route, optimize the initial logistics route to obtain the target logistics route for logistics transportation.

[0087] The number of nodes can refer to the number of customer nodes / supplier nodes included in each initial logistics route, for example, 5, 10, 20, etc.

[0088] For details, please refer to Figure 5 The server 200 can use the order information, location information, and location distance-time matrix information calculated based on the location information of the nodes to be planned (such as the vehicle travel time and distance between the supplier node location and the customer node location; or the vehicle travel time and distance between the supplier node location and the manufacturer node location) as input data for route planning. After combining the three-dimensional loading algorithm and the route planning algorithm to analyze and obtain the initial logistics route of the nodes to be planned, the route feasibility can be further improved and logistics transportation costs can be saved, that is, the initial logistics route can be optimized.

[0089] More specifically, this application proposes that after analyzing and obtaining multiple initial logistics routes for nodes to be planned, or analyzing and obtaining multiple initial logistics routes corresponding to each node to be planned, when faced with more than one initial logistics route, further screening and optimization can be performed to reduce logistics transportation costs. See the following embodiments for details.

[0090] In one embodiment, this step includes: obtaining the number of nodes contained in each initial logistics route; determining the routes to be deleted in each initial logistics route based on the number of nodes, wherein the number of nodes in the routes to be deleted is the minimum value among the number of nodes; if the routes to be deleted contain nodes to be planned, then obtaining a set of routes that do not contain routes to be deleted, and optimizing the initial logistics routes based on the set of routes to obtain the target logistics routes for logistics transportation.

[0091] Specifically, the following steps can be used to optimize the initial logistics route and obtain the target logistics route: (1) After determining the number of nodes in each initial logistics route, remove the route C with the fewest nodes and store the removed nodes in the "ejection pool". Mark the set of routes with removed route C as S′. S′ can also have only one initial logistics route remaining; (2) Select a customer node from the "ejection pool" and find a feasible insertion position from S′. After finding the position, insert the corresponding node to form a new route set S″; (3) If there is no feasible insertion position, insert randomly. At this time, the new route set S″ is an infeasible solution. At this time, S″ will be repaired. The repair algorithm can use the node swap algorithm, that is, swap the two nodes of the two routes. See details. Figure 6 As shown, the infeasible solution is repaired; (4) If the infeasible solution S″ is successfully repaired, repeat steps 2 and 3 until all nodes in the "ejection pool" are inserted; if the infeasible solution S″ is not successfully repaired, then add the current node back to the "ejection pool", select other nodes in the "ejection pool" and repeat steps 2 and 3; (5) If all nodes in the "ejection pool" are inserted, then the optimized initial logistics line can be output as the target logistics line; if there are still nodes that have not been inserted, then the initial logistics line needs to be determined as the target logistics line of the corresponding node to be planned.

[0092] In the logistics transportation method described above, the server obtains the order information and location information of the nodes to be planned. Based on a preset 3D loading algorithm that includes 3D loading constraints, it analyzes the order information and location information to obtain an initial logistics route that satisfies the 3D loading constraints. Then, based on the number of nodes included in each initial logistics route, the server optimizes the initial logistics route to obtain the target logistics route for logistics transportation. Because this application uses a loading algorithm that dynamically generates placement points to treat 3D loading constraints as a hard condition for route planning during the logistics transportation process, it can effectively avoid situations where loading is impossible during actual route implementation. This not only meets the timeliness requirements of logistics transportation tasks but also improves the loading rate of logistics transportation tasks. Therefore, using this method to plan reasonable routes for logistics transportation tasks avoids the problem of goods being suspended or overloaded in logistics transportation vehicles, saving logistics transportation costs and improving logistics transportation efficiency.

[0093] To better implement the logistics transportation method in the embodiments of this application, in such cases... Figure 2 Based on the logistics transportation method shown, this application embodiment also provides a logistics transportation device, such as... Figure 7 As shown, the logistics transportation device 700 includes:

[0094] The information acquisition module 710 is used to acquire the order information and location information of the node to be planned;

[0095] The route planning module 720 is used to analyze order information and location information based on a preset three-dimensional loading algorithm that includes three-dimensional loading constraints, and obtain an initial logistics route that satisfies the three-dimensional loading constraints.

[0096] The route optimization module 730 is used to optimize the initial logistics route based on the number of nodes contained in each initial logistics route, so as to obtain the target logistics route for logistics transportation.

[0097] Specifically, the information acquisition module 710 mentioned above can be called the IO module. The IO module can manage input data information and output result information. The input data information includes, but is not limited to, the order information and location information of the node to be planned. The output result information is the initial logistics route or target logistics route of the node to be planned. The route planning module 720 and the route optimization module 730 mentioned above are collectively referred to as the algorithm module. The algorithm module includes, but is not limited to, the constraint information module, the objective information module, the route information module, the initial solution module, the improved algorithm module, and the bin packing algorithm module.

[0098] The processing steps of each module are as follows: (1) Data from the IO module flows into the algorithm module; (2) The InitialSolution module initializes the nodes to be accessed (one node is one location); (3) The Route module is called, and the Constraint module determines whether unaccessed nodes can be added to the path. The node to be added to the path is selected according to the optimal solution priority strategy, and the Route module and Objective module are updated at the same time; (4) Steps 2 and 3 are repeated until all nodes are accessed. At this time, all paths are used as the initial solution of the algorithm (initial logistics route); (5) The Algorithm module is called, and the initial solution is improved with the ejection pool algorithm. The maximum number of iterations is set to terminate the algorithm, and the final result is output and stored in the IO module.

[0099] In some embodiments of this application, the information acquisition module 710 is further configured to acquire pickup plan information or delivery plan information of the node to be planned, the pickup plan information or delivery plan information including cargo parameter information and logistics timeliness; process the information format of the pickup plan information or delivery plan information to obtain the order information of the node to be planned; and acquire the cargo transportation address in the pickup plan information or delivery plan information to obtain the location information of the node to be planned.

[0100] In some embodiments of this application, the route planning module 720 is further configured to obtain vehicle working time and vehicle capacity information corresponding to the currently available routes when the node to be planned is not empty; analyze order information, location information, vehicle working time and / or vehicle capacity information based on a preset three-dimensional loading algorithm containing three-dimensional loading constraints, and obtain analysis results; and select target routes from the currently available routes as initial logistics routes based on the analysis results.

[0101] In some embodiments of this application, the route planning module 720 is further configured to determine an objective function for planning a logistics route, wherein the objective function is a first objective function and / or a second objective function; if the objective function is a first objective function and a second objective function, the route planning information is analyzed in combination with the objective function and objective constraints according to the preset priority of each objective function, and the vehicle working time and / or vehicle capacity information is analyzed to obtain the analysis result; wherein the route planning information includes order information and location information; if the objective function is a first objective function or a second objective function, the route planning information is analyzed in combination with the objective function and objective constraints, and the vehicle working time and / or vehicle capacity information is analyzed to obtain the analysis result; wherein the objective constraints include three-dimensional loading constraints, as well as preset time window constraints and / or capacity constraints.

[0102] In some embodiments of this application, the objective function further includes a third objective function. The order information includes cargo parameter information and logistics time. The route planning module 720 is also used to analyze the route planning information by combining the objective function and objective constraints, and to analyze the vehicle working time and / or vehicle capacity information to obtain the cargo loading planning result. If the cargo loading planning result satisfies the objective function and objective constraints, the analysis result is determined as the first analysis result. If the cargo loading planning result does not satisfy the objective function or objective constraints, the initialized empty route is obtained, and when the logistics cost value of the node to be planned in the empty route does not meet the preset cost conditions, the analysis result is determined as the second analysis result.

[0103] In some embodiments of this application, the route planning module 720 is further configured to: if the analysis result is the first analysis result, use the corresponding currently available route as the target route; obtain the route code of the target route; and based on the route code, filter out the target route among the currently available routes as the initial logistics route.

[0104] In some embodiments of this application, the route optimization module 730 is further configured to obtain the number of nodes contained in each initial logistics route; based on the number of nodes, determine the routes to be deleted in each initial logistics route, wherein the number of nodes in the routes to be deleted is the minimum value among the number of nodes; if the routes to be deleted contain nodes to be planned, obtain a set of routes that do not contain routes to be deleted, and optimize the initial logistics routes based on the set of routes to obtain a target logistics route that satisfies the cargo parameter information and logistics timeliness.

[0105] In the above embodiments, because this application uses a loading algorithm that dynamically generates placement points to make three-dimensional loading constraints a hard condition for route planning during the logistics transportation process, it can effectively avoid situations where loading is impossible during actual route implementation. This not only meets the timeliness requirements of logistics transportation tasks but also improves the loading rate of logistics transportation tasks. Therefore, using this method to plan reasonable routes for logistics transportation tasks avoids the problems of goods being suspended or overloaded in logistics transportation vehicles, saving logistics transportation costs and improving logistics transportation efficiency.

[0106] Specific limitations regarding logistics transportation devices can be found in the limitations regarding logistics transportation methods described above, and will not be repeated here. Each module in the aforementioned logistics transportation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0107] In some embodiments of this application, the logistics transportation device 700 can be implemented as a computer program, which can be implemented in, for example... Figure 8 The computer device shown runs on this system. The computer device's memory can store the various program modules that make up the logistics transportation device 700, for example, Figure 8 The information acquisition module 710, route planning module 720, and route optimization module 730 are shown. The computer program comprised of these modules causes the processor to execute the steps of the logistics transportation methods described in the various embodiments of this application.

[0108] For example, Figure 8 The computer equipment shown can be used as follows Figure 8 The information acquisition module 710 in the logistics transportation device 700 shown executes step S201. The computer device can execute step S202 via the route planning module 720. The computer device can execute step S203 via the route optimization module 730. The computer device includes a processor, memory, and a network interface connected via a system bus. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communication with external computer devices via a network connection. When the computer program is executed by the processor, it implements a logistics transportation method.

[0109] Those skilled in the art will understand that Figure 8The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0110] In some embodiments of this application, a computer device is provided, including one or more processors; a memory; and one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the processors as described in the logistics transportation method. The steps of the logistics transportation method here may be steps from the logistics transportation methods of the various embodiments described above.

[0111] In some embodiments of this application, a computer-readable storage medium is provided, storing a computer program that is loaded by a processor, causing the processor to execute the steps of the above-described logistics transportation method. The steps of this logistics transportation method may be those found in the logistics transportation methods of the various embodiments described above.

[0112] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. 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.

[0113] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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, they should be considered to be within the scope of this specification.

[0114] The above provides a detailed description of a logistics transportation method, apparatus, computer equipment, and storage medium provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, those skilled in the art will recognize that there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A logistics transportation method, characterized in that, include: Obtain order and location information for the nodes to be planned; Based on a preset 3D loading algorithm incorporating 3D loading constraints, the order information and location information are analyzed to obtain an initial logistics route that satisfies the 3D loading constraints; wherein, the process of analyzing the order information and location information based on the preset 3D loading algorithm incorporating 3D loading constraints to obtain an initial logistics route that satisfies the 3D loading constraints includes: If the node to be planned is not empty, obtain the vehicle working time and vehicle capacity information corresponding to the currently available route; Based on a preset 3D loading algorithm that includes 3D loading constraints, the order information, the location information, the vehicle working time and / or the vehicle capacity information are analyzed to obtain the analysis results. Based on the analysis results, the target route among the currently available routes is selected as the initial logistics route; Based on the number of nodes to be planned in each initial logistics route, routes to be deleted in each initial logistics route are determined. If a route to be deleted contains a node to be planned, a set of routes that do not contain the route to be deleted is obtained. Based on the set of routes, the initial logistics routes are optimized to obtain target logistics routes for logistics transportation, which include: (1) Determine the number of planned nodes for each initial logistics route, remove the initial logistics route C with the fewest planned nodes, and store the removed planned nodes in the ejection pool. Mark the set of routes where C has been removed as S′; (2) Select a planned node from the ejection pool, find an insertion position from S′, and insert the planned node at the corresponding insertion position to form a first new route set; (3) If there is no feasible insertion position, perform a random insertion operation to form a second new route set, and repair the second new route set; (4) If the second If the new route set is successfully repaired, repeat steps (2) and (3) until all the planned nodes in the ejection pool are inserted; if the second new route set is not successfully repaired, add the current planned node back to the ejection pool, select other planned nodes in the ejection pool, and repeat steps (2) and (3); (5) If all the planned nodes in the ejection pool are inserted, output the optimized initial logistics route as the target logistics route; if there are still planned nodes that have not been inserted, determine the initial logistics route as the target logistics route of the planned node.

2. The method as described in claim 1, characterized in that, The three-dimensional loading algorithm based on a preset three-dimensional loading constraint analyzes the order information, the location information, the vehicle working time and / or the vehicle capacity information to obtain the analysis results, including: Determine the objective function for planning logistics routes, wherein the objective function is a first objective function and / or a second objective function; If the objective function is the first objective function and the second objective function, then the route planning information is analyzed according to the preset priority of each objective function, combined with the objective function and objective constraints, and the vehicle working time and / or the vehicle capacity information are analyzed to obtain the analysis result; wherein, the route planning information includes the order information and the location information; If the objective function is the first objective function or the second objective function, then the route planning information is analyzed in combination with the objective function and the objective constraints, and the vehicle working time and / or the vehicle capacity information are analyzed to obtain the analysis results; wherein, the objective constraints include the three-dimensional loading constraints, as well as preset time window constraints and / or capacity constraints.

3. The method as described in claim 2, characterized in that, The objective function also includes a third objective function. The order information includes cargo parameter information and logistics delivery time. The analysis of the route planning information, the vehicle working time and / or the vehicle capacity information, is combined with the objective function and the objective constraints to obtain the analysis results, including: By combining the objective function and the objective constraints to analyze the route planning information, and by analyzing the vehicle working time and / or the vehicle capacity information, the cargo loading planning results are obtained. If the cargo loading planning result satisfies the objective function and the objective constraint, then the analysis result is determined as the first analysis result; If the cargo loading planning result does not meet the objective function or the objective constraint, then an initialized empty route is obtained, and when the logistics cost value of the node to be planned in the empty route does not meet the preset cost condition, the analysis result is determined as the second analysis result.

4. The method as described in claim 1, characterized in that, Based on the analysis results, the process of selecting target routes from the currently available routes as the initial logistics route includes: If the analysis result is the first analysis result, then the corresponding currently available line will be used as the target line; Obtain the line code of the target line; Based on the route code, the target route among the currently available routes is selected as the initial logistics route.

5. The method according to any one of claims 1-3, characterized in that, The process of obtaining the order information and location information of the node to be planned includes: Obtain pickup or delivery plan information for the nodes to be planned; The information format of the pickup plan information or the delivery plan information is processed to obtain the order information of the node to be planned; Obtain the cargo transportation address from the pickup plan information or the delivery plan information to obtain the location information of the node to be planned.

6. A logistics transportation device, characterized in that, include: The information acquisition module is used to acquire order information and location information of the nodes to be planned; The route planning module is used to analyze the order information and the location information based on a preset three-dimensional loading algorithm containing three-dimensional loading constraints, and obtain an initial logistics route that satisfies the three-dimensional loading constraints; wherein, the route planning module is specifically used to: obtain the vehicle working time and vehicle capacity information corresponding to the currently available route when the node to be planned is not empty; Based on a preset 3D loading algorithm that includes 3D loading constraints, the order information, the location information, the vehicle working time and / or the vehicle capacity information are analyzed to obtain the analysis results. Based on the analysis results, the target route among the currently available routes is selected as the initial logistics route; The route optimization module is used to determine the routes to be deleted in each of the initial logistics routes based on the number of nodes to be planned in each of the initial logistics routes. If the route to be deleted contains the nodes to be planned, a set of routes that do not contain the route to be deleted is obtained, and the initial logistics routes are optimized based on the set of routes to obtain the target logistics routes for logistics transportation. The line optimization module is specifically used for: (1) Determine the number of planned nodes for each initial logistics route, remove the initial logistics route C with the fewest planned nodes, and store the removed planned nodes in the ejection pool. Mark the set of routes where C has been removed as S′; (2) Select a planned node from the ejection pool, find an insertion position from S′, and insert the planned node at the corresponding insertion position to form a first new route set; (3) If there is no feasible insertion position, perform a random insertion operation to form a second new route set, and repair the second new route set; (4) If the second If the new route set is successfully repaired, repeat steps (2) and (3) until all the planned nodes in the ejection pool are inserted; if the second new route set is not successfully repaired, add the current planned node back to the ejection pool, select other planned nodes in the ejection pool, and repeat steps (2) and (3); (5) If all the planned nodes in the ejection pool are inserted, output the optimized initial logistics route as the target logistics route; if there are still planned nodes that have not been inserted, determine the initial logistics route as the target logistics route of the planned node.

7. A computer device, characterized in that, The computer device includes: One or more processors; The memory; and one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the logistics transportation method of any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, It stores a computer program, which is loaded by a processor to execute the steps of the logistics transportation method according to any one of claims 1 to 5.

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