A short-distance logistics management method and system supporting instant handover

Abstract

The present invention discloses a short-distance logistics management method and system that supports instant handover, relating to the field of logistics data management technology. The method comprises: identifying instant handover nodes based on short-distance logistics tasks to generate an instant logistics handover chain; jointly scheduling multi-node logistics resources to establish a first logistics resource scheduling space; performing evaluation and inspection optimization to generate a second logistics resource scheduling space; performing variation and expansion to obtain a third logistics resource scheduling space; performing optimal maximization of logistics scheduling to generate a logistics resource scheduling optimization strategy; and executing short-distance logistics tasks based on the logistics instant handover chain and the logistics resource scheduling optimization strategy. The method solves the technical problems of low scheduling efficiency, irrational resource allocation, and lagging handover node management in the prior art for short-distance logistics tasks, thereby achieving the technical effects of improving task execution efficiency, enhancing management flexibility, and increasing the level of intelligence.

Description

Technical Field

[0001] The present application relates to the technical field related to logistics data management, and specifically to a short-distance logistics management method and system supporting instant handover. Background Art

[0002] Short-haul logistics involves the transportation of goods from one location to another. Its key characteristics are short distances, frequent handovers, and strict time constraints. Efficiently managing and scheduling short-haul logistics resources to ensure the fastest possible delivery and improve resource utilization has become a pressing technical challenge in the logistics industry. Traditional short-haul logistics management methods often rely on manual scheduling, which is inefficient, subject to information lags, and uneven resource allocation, leading to numerous bottlenecks in the logistics process. For example, with numerous logistics tasks and numerous handover nodes, dispatchers are unable to keep track of the real-time status of all logistics resources, making optimal scheduling difficult.

[0003] Therefore, at the current stage, relevant technologies have technical problems such as low efficiency in short-distance logistics task scheduling, unreasonable resource allocation, and lagging handover node management. Summary of the Invention

[0004] This application solves the technical problems of low efficiency in short-distance logistics task scheduling, unreasonable resource allocation, and lagging handover node management in the existing technology by providing a short-distance logistics management method and system that supports instant handover, and achieves the technical effect of improving task execution efficiency, enhancing management flexibility and intelligence level.

[0005] The present application provides a short-distance logistics management method that supports instant handover, the method comprising: identifying instant handover nodes according to short-distance logistics tasks to generate a logistics instant handover chain; jointly scheduling multi-node logistics resources for the short-distance logistics tasks according to the logistics instant handover chain to establish a first logistics resource scheduling space; introducing a logistics scheduling evaluation and inspection channel to evaluate and inspect the first logistics resource scheduling space to seek an optimization to generate a second logistics resource scheduling space; mutating and expanding the second logistics resource scheduling space according to logistics scheduling variation constraint rules to obtain a third logistics resource scheduling space; maximizing the logistics scheduling optimality of the third logistics resource scheduling space according to a logistics scheduling optimality parser to generate a logistics resource scheduling optimization strategy; executing the short-distance logistics task according to the logistics instant handover chain and the logistics resource scheduling optimization strategy.

[0006] In a possible implementation, the short-distance logistics management method that supports instant handover also performs the following processing: collecting logistics resource information based on the logistics instant handover chain to obtain multiple node logistics resource data sets; organizing the multiple node logistics resource data sets to establish multiple node logistics resource spaces; scheduling logistics resources for the short-distance logistics tasks based on the multiple node logistics resource spaces to obtain multiple node logistics resource scheduling decision sets; combining multiple node logistics resource scheduling decisions based on the multiple node logistics resource scheduling decision sets to generate the first logistics resource scheduling space.

[0007] In a possible implementation, the short-distance logistics management method that supports instant handover also performs the following processing: the logistics scheduling evaluation and inspection channel includes a logistics scheduling evaluator and a logistics scheduling verifier; traverses the first logistics resource scheduling space to extract the first logistics resource scheduling plan; inputs the first logistics resource scheduling plan into the logistics scheduling evaluator to obtain a first logistics scheduling evaluation result, wherein the logistics scheduling evaluator includes a logistics scheduling timeliness evaluation model, a logistics resource utilization evaluation model and a logistics cargo loss evaluation model; inputs the first logistics scheduling evaluation result into the logistics scheduling verifier to obtain a first logistics scheduling inspection result; when the first logistics scheduling inspection result is unqualified, eliminate the first logistics resource scheduling plan; when the first logistics scheduling inspection result is qualified, add the first logistics resource scheduling plan to the second logistics resource scheduling space.

[0008] In a possible implementation, the short-distance logistics management method that supports instant handover also performs the following processing: the logistics scheduling verifier includes a logistics scheduling verification operator, and the logistics scheduling verification operator includes: if the first logistics scheduling evaluation result meets the logistics scheduling evaluation constraints, the first logistics scheduling verification result is qualified, wherein the logistics scheduling evaluation constraints include logistics scheduling timeliness constraints, logistics resource utilization constraints and logistics cargo loss constraints; if the first logistics scheduling evaluation result does not meet the logistics scheduling evaluation constraints, the first logistics scheduling verification result is unqualified.

[0009] In a possible implementation, the short-distance logistics management method that supports instant handover also performs the following processing: calculating the variation characteristic parameters of the second space of logistics resource scheduling according to the logistics scheduling variation constraint rules to obtain the logistics scheduling variation characteristic distribution; mutating the second space of logistics resource scheduling according to the logistics scheduling variation characteristic distribution to obtain the logistics resource scheduling variation space; evaluating and testing the logistics resource scheduling variation space according to the logistics scheduling evaluation and inspection channel to generate the logistics resource scheduling variation optimization space; expanding the second space of logistics resource scheduling according to the logistics resource scheduling variation optimization space to obtain the third space of logistics resource scheduling.

[0010] In a possible implementation, the short-distance logistics management method that supports instant handover also performs the following processing: the logistics scheduling variation constraint rules include the logistics scheduling variation basic quantity; extracting the nth logistics resource scheduling plan in the second space of the logistics resource scheduling, where n is a positive integer; loading the nth logistics scheduling evaluation result corresponding to the nth logistics resource scheduling plan according to the logistics scheduling evaluation inspection channel; performing variation value evaluation on the nth logistics resource scheduling plan according to the nth logistics scheduling evaluation result to obtain the variation value coefficient of the nth plan; performing incentive adjustment on the logistics scheduling variation basic quantity according to the nth plan variation value coefficient to generate the nth variation feature quantity, and adding the nth variation feature quantity to the logistics scheduling variation feature distribution.

[0011] In a possible implementation, the short-distance logistics management method supporting instant delivery further performs the following processing: the logistics scheduling optimality parser includes a logistics scheduling optimality parsing function, and the logistics scheduling optimality parsing function is: ;

[0012] Among them, OLS represents the optimality of logistics scheduling, OLK represents the analytical factor of the optimality of logistics scheduling, OLK>1, G(TES) represents the normalized timeliness of logistics scheduling, TESW represents the timeliness-weight of logistics scheduling, G(LRX) represents the normalized logistics resource utilization, LRXW represents the logistics resource utilization-weight, G(LCX) represents the normalized logistics cargo loss coefficient, and LCXW represents the logistics cargo loss weight.

[0013] The present application also provides a short-distance logistics management system that supports instant handover, including: an instant handover node identification module, which is used to identify instant handover nodes according to short-distance logistics tasks and generate a logistics instant handover chain; a logistics resource joint scheduling module, which is used to perform multi-node logistics resource joint scheduling for the short-distance logistics tasks according to the logistics instant handover chain, and establish a first logistics resource scheduling space; an evaluation, inspection and optimization module, which is used to introduce a logistics scheduling evaluation and inspection channel to evaluate, inspect and optimize the first logistics resource scheduling space, and generate a second logistics resource scheduling space; a mutation and expansion module, which is used to perform mutation and expansion on the second logistics resource scheduling space according to the logistics scheduling mutation constraint rules, and obtain a third logistics resource scheduling space; a scheduling optimization strategy generation module, which is used to perform logistics scheduling optimal maximization optimization on the third logistics resource scheduling space according to a logistics scheduling optimality analyzer, and generate a logistics resource scheduling optimization strategy; a short-distance logistics task execution module, which is used to execute the short-distance logistics task according to the logistics instant handover chain and the logistics resource scheduling optimization strategy.

[0014] This application proposes a short-distance logistics management method and system that supports instant handover. The system identifies instant handover nodes based on short-distance logistics tasks and generates an instant logistics handover chain. It also performs multi-node joint scheduling of logistics resources to establish a first logistics resource scheduling space. It performs evaluation and testing to optimize and generate a second logistics resource scheduling space. It performs variation and expansion to obtain a third logistics resource scheduling space. It performs optimal maximization of logistics scheduling to generate a logistics resource scheduling optimization strategy. The system then executes short-distance logistics tasks based on the instant logistics handover chain and the logistics resource scheduling optimization strategy. This system addresses the existing technical issues of low short-distance logistics task scheduling efficiency, irrational resource allocation, and lagging handover node management, achieving the technical benefits of improving task execution efficiency, enhancing management flexibility, and increasing intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the accompanying drawings of the embodiments of the present disclosure are briefly introduced below. Flowcharts are used in this application to illustrate the operations performed by the systems according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in precise order. Instead, various steps may be processed in reverse order or simultaneously as needed. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0016] Figure 1 A flowchart of a short-distance logistics management method supporting instant delivery provided in an embodiment of the present application;

[0017] Figure 2 A schematic diagram of the structure of a short-distance logistics management system supporting instant handover provided in an embodiment of the present application.

[0018] Explanation of the accompanying symbols: instant handover node identification module 10, logistics resource joint scheduling module 20, evaluation and inspection optimization module 30, variation and expansion module 40, scheduling optimization strategy generation module 50, short-distance logistics task execution module 60. DETAILED DESCRIPTION

[0019] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0020] In order to make the purpose, technical solutions and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0021] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict, and the terms “first\second” involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. The terms “including” and “having” and any variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or that are inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used herein are for the purpose of describing the embodiments of this application only.

[0022] The embodiment of the present application provides a short-distance logistics management method that supports instant delivery, such as Figure 1 As shown, the method includes:

[0023] Step S100: Identify the instant handover nodes according to the short-distance logistics task and generate the logistics instant handover chain.

[0024] Preferably, during the execution of short-distance logistics tasks, the handover nodes between different links of the goods are accurately determined according to the specific needs and actual conditions of the tasks. The immediate handover nodes may be logistics centers, distribution sites, warehouses, transport vehicles, etc. Specifically, when identifying immediate handover nodes, multiple factors need to be considered, including but not limited to, cargo characteristics (the type, size, weight and other characteristics of the cargo will affect the selection of handover nodes), transportation methods (different transportation methods, such as road, rail, and air, may correspond to different handover nodes), time requirements (the time requirements of the logistics tasks will affect the selection of handover nodes), cost considerations (the selection of handover nodes also needs to consider cost factors, including transportation costs). , warehousing costs, etc.), and after identifying the instant handover nodes, a logistics instant handover chain is generated. This means connecting each instant handover node in the order in which the logistics tasks are executed to form a complete logistics chain, covering the entire process from the departure of the goods to their final delivery to the customer, including the handover and transportation of each link. Specifically, generating a logistics instant handover chain includes determining the order of each handover node based on the execution order of the logistics tasks; planning the optimal transportation route based on the geographical location and traffic conditions of the nodes; setting specific time requirements for each handover node to ensure that the logistics tasks can be completed on time; and rationally allocating logistics resources, such as transport vehicles and personnel, based on the needs of the nodes and the scale of the logistics tasks. By accurately identifying handover nodes and generating logistics instant handover chains, comprehensive monitoring and management of short-distance logistics tasks can be achieved, helping to ensure that logistics tasks can be smoothly executed according to the predetermined schedule and route, thereby improving logistics efficiency and service quality.

[0025] Step S200: performing multi-node logistics resource joint scheduling for the short-distance logistics task according to the logistics instant handover chain, and establishing a first logistics resource scheduling space.

[0026] Preferably, multi-node logistics resources are jointly dispatched for short-distance logistics tasks based on the generated logistics instant handover chain, that is, the logistics resources required by each handover node are reasonably dispatched and allocated, wherein the logistics resources include but are not limited to transport vehicles, loading and unloading equipment, storage space, personnel, etc. Specifically, according to the needs and characteristics of each node in the logistics instant handover chain and the overall requirements of the logistics tasks, the logistics resources are uniformly managed and optimized. For example, each handover node has specific functions and needs in the logistics instant handover chain, such as loading and unloading goods, temporary storage, cargo sorting, etc., and the corresponding logistics resources need to be dispatched according to the specific needs of the node; when dispatching logistics resources, the availability of resources also needs to be considered, such as the number, type, location, etc. of transport vehicles, as well as the personnel. Skill level, work experience, etc.; logistics tasks have strict time requirements and need to be completed within the specified time. When scheduling logistics resources, time factors must also be considered to ensure that logistics activities between various nodes can be closely connected to avoid delays. Then, based on the results of the joint scheduling of multi-node logistics resources, a first logistics resource scheduling space is established to uniformly manage and monitor logistics resources. Specifically, the logistics resource scheduling first space displays currently available logistics resources, such as the location, status, and type of transport vehicles, as well as the skill level and work schedule of personnel. Based on the needs and resource availability of each node in the logistics instant handover chain, specific logistics tasks are assigned to the corresponding resources. The operating status of logistics resources and task execution are monitored in real time, and timely adjustments and optimizations are made as needed. By establishing the first logistics resource scheduling first space, comprehensive management and optimization of logistics resources can be achieved, improving logistics efficiency and service quality.

[0027] Furthermore, step S200 also includes step S210, collecting logistics resource information according to the logistics instant handover chain to obtain multiple node logistics resource data sets; step S220, organizing the multiple node logistics resource data sets to establish multiple node logistics resource spaces; step S230, scheduling logistics resources for the short-distance logistics tasks according to the multiple node logistics resource spaces to obtain multiple node logistics resource scheduling decision sets; step S240, combining multiple node logistics resource scheduling decisions according to the multiple node logistics resource scheduling decision sets to generate the first logistics resource scheduling space.

[0028] Preferably, a variety of logistics resource information is collected and obtained based on the logistics instant handover chain, which may include node information (such as the location, capacity, working hours, etc. of warehouses, loading and unloading points, transfer stations, etc.), transportation tool information (such as the type, number, load capacity, driving speed, available time, etc. of vehicles, ships, aircraft, etc.), and cargo information (such as the type, quantity, size, weight, destination, delivery time, etc. of cargo), to form multiple node logistics resource data sets; the multiple node logistics resource data sets are sorted and analyzed, including the logistics resource information of each node (such as warehouses, loading and unloading points, etc.), and then multiple node logistics resource spaces are established to represent the distribution and status of logistics resources at each node. By establishing these spaces, the distribution and utilization of logistics resources can be more intuitively understood; then, the multiple node logistics resource data sets established are used to analyze the logistics resource information of each node (such as warehouses, loading and unloading points, etc.). Point logistics resource space, logistics resource scheduling for short-distance logistics tasks may involve multiple considerations, such as cost, time, efficiency, safety, etc., that is, through algorithm optimization and data analysis, appropriate logistics resources are allocated to each node to meet the needs of short-distance logistics tasks, and then multiple node logistics resource scheduling decision sets are output. Each decision set contains a resource scheduling plan for a specific node; finally, the multiple node logistics resource scheduling decision sets are combined and optimized to form an overall logistics resource scheduling plan, that is, the first logistics resource scheduling space, including multiple logistics resource scheduling plans. Each logistics resource scheduling plan includes multiple node logistics resource scheduling decisions corresponding to multiple logistics instant handover nodes, so as to carry out logistics resource scheduling more scientifically and efficiently, and improve logistics efficiency and service quality.

[0029] Step S300: introducing a logistics scheduling evaluation and inspection channel to evaluate and inspect the first logistics resource scheduling space to find the best solution, and generating a second logistics resource scheduling space.

[0030] Preferably, the logistics scheduling evaluation and inspection channel is used to evaluate and inspect the first space of logistics resource scheduling to find the best, that is, the initially formed logistics resource scheduling plan (that is, the first space of logistics resource scheduling) is comprehensively evaluated through multiple evaluation and inspection indicators, and then a more efficient and reasonable logistics resource scheduling plan (that is, the second space of logistics resource scheduling) is obtained. Among them, the logistics scheduling evaluation and inspection channel is used to comprehensively evaluate the resource allocation, task execution, time management, cost control and other aspects in the first space of logistics resource scheduling. Specifically, the logistics scheduling evaluation and inspection channel is used to evaluate and inspect the first space of logistics resource scheduling to find the problems and deficiencies in the first space of logistics resource scheduling, and propose improvement plans, and then optimize the second space of logistics resource scheduling, that is, the new logistics resource scheduling plan. Compared with the first space of logistics resource scheduling, the second space has significant improvements in resource utilization efficiency, task execution efficiency, cost control and other aspects, which helps to achieve the optimal allocation and efficient utilization of logistics resources.

[0031] Furthermore, step S300 also includes step S310, wherein the logistics scheduling evaluation and inspection channel includes a logistics scheduling evaluator and a logistics scheduling verifier; step S320, traversing the first logistics resource scheduling space and extracting the first logistics resource scheduling plan; step S330, inputting the first logistics resource scheduling plan into the logistics scheduling evaluator to obtain a first logistics scheduling evaluation result, wherein the logistics scheduling evaluator includes a logistics scheduling timeliness evaluation model, a logistics resource utilization evaluation model and a logistics cargo loss evaluation model; step S340, inputting the first logistics scheduling evaluation result into the logistics scheduling verifier to obtain a first logistics scheduling inspection result; step S350, when the first logistics scheduling inspection result is unqualified, eliminating the first logistics resource scheduling plan; step S360, when the first logistics scheduling inspection result is qualified, adding the first logistics resource scheduling plan to the second logistics resource scheduling space.

[0032] Preferably, the logistics scheduling evaluation and inspection channel includes a logistics scheduling evaluator and a logistics scheduling verifier, wherein the logistics scheduling evaluator is used to conduct a comprehensive and objective evaluation of the logistics resource scheduling plan, and includes multiple evaluation models, such as a logistics scheduling timeliness evaluation model (evaluation of the time efficiency of the plan), a logistics resource utilization evaluation model (evaluation of the resource utilization efficiency of the plan) and a logistics cargo loss evaluation model (evaluation of the plan's ability to protect cargo during transportation), and the logistics scheduling verifier is used to further inspect the output results of the evaluator to determine whether the plan meets the established standards and requirements; traverse the first logistics resource scheduling space and randomly extract a logistics resource scheduling plan from it as the first logistics resource scheduling plan, and then input the extracted first logistics resource scheduling plan into the logistics scheduling evaluator, and use the various evaluation models in the logistics scheduling evaluator to comprehensively evaluate the plan to obtain the first logistics scheduling evaluation result, which includes the plan's timeliness, resource utilization, and the first logistics scheduling evaluation result. and cargo loss, etc.; then the first logistics scheduling evaluation result is input into the logistics scheduling verifier for further inspection to determine whether the plan meets the established standards and requirements, such as whether the predetermined time efficiency, resource utilization efficiency and cargo protection level are achieved, and then the first logistics scheduling inspection result is obtained; then it is judged whether the first logistics scheduling inspection result is qualified. If the first logistics scheduling inspection result is unqualified, that is, the plan fails to meet the established standards and requirements, the first logistics resource scheduling plan is eliminated, which means that the plan is not suitable as the final logistics resource scheduling plan; if the first logistics scheduling inspection result is qualified, that is, the plan meets the established standards and requirements, the first logistics resource scheduling plan is added to the second logistics resource scheduling space for storing qualified logistics resource scheduling plans that have been evaluated and inspected, to ensure that the selected plan performs well in terms of timeliness, resource utilization and cargo loss, thereby improving logistics efficiency and service quality.

[0033] Preferably, the logistics scheduling timeliness evaluation model focuses on the time efficiency of the logistics scheduling plan. Specifically, the core indicators of timeliness evaluation are determined, including transportation time, distribution time, response time, etc. The time data of transportation, distribution, response, etc. are collected in real time through the logistics information system, and cleaned, sorted and analyzed to ensure the accuracy and reliability of the data. Based on the collected data, appropriate algorithms and models (such as time series analysis, regression analysis, etc.) are used to evaluate timeliness, so that the model can comprehensively consider the impact of various factors on time efficiency, such as traffic conditions, weather conditions, human resources, etc.; the logistics resource utilization evaluation model focuses on the effective utilization of resources by the logistics scheduling plan. Specifically, the types of logistics resources are clarified, including transportation tools, storage facilities, human resources, etc., and then the evaluation indicators of resource utilization are determined, including vehicle load rate, warehouse space utilization, human resource utilization efficiency, etc., to reflect the utilization and efficiency of resources. Through the logistics information system Resource usage data is collected in real time and analyzed and processed to evaluate the actual situation of resource utilization. Appropriate algorithms and models (such as data envelopment analysis and fuzzy comprehensive evaluation) are used to evaluate resource utilization, so that the model can comprehensively consider the impact of various factors on resource utilization, such as the selection of transportation tools and the layout of storage facilities. The logistics cargo loss evaluation model mainly focuses on the ability of logistics scheduling plans to protect cargo during transportation. Specifically, it identifies cargo loss factors such as natural disasters, traffic accidents, improper packaging, etc., and then determines the evaluation indicators of cargo loss, including cargo loss rate and cargo integrity rate. Cargo loss data is collected in real time through the logistics information system and analyzed and processed to evaluate the actual situation of cargo loss. Then, appropriate algorithms and models (such as probability statistics and analogy evaluation) are used to evaluate cargo loss, so that the model can comprehensively consider the impact of various factors on cargo loss, such as the choice of transportation route and the selection of packaging materials.

[0034] Furthermore, step S300 also includes step S370, and the logistics scheduling verifier includes a logistics scheduling verification operator, and the logistics scheduling verification operator includes: A: If the first logistics scheduling evaluation result meets the logistics scheduling evaluation constraints, the first logistics scheduling verification result is qualified, wherein the logistics scheduling evaluation constraints include logistics scheduling timeliness constraints, logistics resource utilization constraints and logistics cargo loss constraints; B: If the first logistics scheduling evaluation result does not meet the logistics scheduling evaluation constraints, the first logistics scheduling verification result is unqualified.

[0035] Preferably, based on the output result of the logistics scheduling evaluator (i.e., the first logistics scheduling evaluation result) and the preset logistics scheduling evaluation constraints, it is judged whether the first logistics resource scheduling plan is qualified. The logistics scheduling verifier uses the logistics scheduling verification operator to evaluate the first logistics scheduling evaluation result to determine whether the first logistics resource scheduling plan meets the established standards and requirements. Among them, the logistics scheduling verification operator includes two main parts. If the first logistics scheduling evaluation result meets the logistics scheduling evaluation constraints, the first logistics scheduling verification result is qualified. The logistics scheduling evaluation constraints are preset to measure whether the logistics resource scheduling plan meets the established standards, specifically including the logistics scheduling timeliness. Constraints (requiring that the logistics scheduling plan be efficient in time, such as transportation time, delivery time, etc. should be within a reasonable range), logistics resource utilization constraints (requiring that the logistics scheduling plan can make full use of existing resources, such as vehicle load rate, warehouse space utilization rate, etc. meet certain standards), and logistics cargo loss constraints (requiring that the logistics scheduling plan can protect the cargo during transportation and reduce cargo loss, such as the cargo loss rate should be controlled within a certain range); if the first logistics scheduling evaluation result does not meet any one or more of the logistics scheduling evaluation constraints, the first logistics scheduling inspection result is unqualified, ensuring that only plans that meet the established standards and requirements can be designated as alternative plans.

[0036] Step S400: mutate and expand the second logistics resource scheduling space according to the logistics scheduling variation constraint rule to obtain a third logistics resource scheduling space.

[0037] Preferably, the second space of logistics resource scheduling is mutated and expanded according to the variation constraint rules of logistics scheduling, that is, by introducing variation operations and constraint rules, on the basis of the existing logistics resource scheduling scheme (i.e., the second space of logistics resource scheduling), the configuration and scheduling of logistics resources are explored and optimized, thereby forming a more efficient and adaptable logistics resource scheduling scheme (i.e., the third space of logistics resource scheduling). Among them, the variation constraint rules refer to the adjustment or change of logistics paths, resource allocation, time windows, etc. in logistics scheduling to cope with uncertainty or optimize existing schemes. The constraint rules ensure that the variation operations are carried out within a reasonable range to avoid infeasible or inefficient situations. Scheduling schemes, such as resource availability, time constraints, customer needs, etc., are selected. Specifically, according to the mutation constraint rules, mutation operations are introduced, including re-planning of logistics routes, adjustment of resource allocation, change of time windows, etc., to explore potential optimization space. Then, the mutated logistics resource scheduling schemes are evaluated to check whether they meet the constraint rules and compare their efficiency, cost and other aspects. If the mutated scheme has improved performance and meets all constraints, it will be regarded as a feasible candidate scheme. After multiple mutations and evaluations, the third space of logistics resource scheduling is generated, thereby further improving the efficiency and adaptability of logistics scheduling.

[0038] Furthermore, step S400 also includes step S410, calculating the variation characteristic parameters of the second logistics resource scheduling space according to the logistics scheduling variation constraint rules to obtain the logistics scheduling variation characteristic distribution; step S420, mutating the second logistics resource scheduling space according to the logistics scheduling variation characteristic distribution to obtain the logistics resource scheduling variation space; step S430, evaluating and testing the logistics resource scheduling variation space according to the logistics scheduling evaluation and inspection channel to generate the logistics resource scheduling variation optimization space; step S440, expanding the second logistics resource scheduling space according to the logistics resource scheduling variation optimization space to obtain the third logistics resource scheduling space.

[0039] Preferably, the variation characteristic parameters of the second space of logistics resource scheduling are calculated according to the variation constraint rules of logistics scheduling (such as the adjustment range of the transportation path, the variation range of resource allocation, etc.), wherein the variation parameters describe the specific changes that may occur in the plan during the variation process, for example, for the adjustment of the transportation path, the change in the path length, the increase or decrease of nodes on the path, etc. are calculated; for the change in resource allocation, the increase or decrease ratio of resources, the change in resource utilization efficiency, etc. are calculated, and then the variation characteristic distribution of logistics scheduling is obtained; based on the variation characteristic distribution of logistics scheduling, the second space of logistics resource scheduling is mutated, that is, if the variation characteristic parameter represents the adjustment of the transportation path, the path is adjusted according to the value of the parameter, such as adding or reducing nodes on the path, changing the order of nodes, etc.; if the variation characteristic parameter represents the change of resource allocation, the resources are reallocated according to the value of the parameter, such as increasing or decreasing the quantity of a certain resource, adjusting the allocation ratio of resources, etc.; the set of mutated plans constitutes the variation space of logistics resource scheduling.

[0040] Preferably, each plan in the logistics resource scheduling variation space is input into the logistics scheduling evaluation and inspection channel for evaluation and inspection. The logistics scheduling evaluator will evaluate each plan in terms of timeliness, resource utilization and cargo loss, and generate corresponding evaluation results. The logistics scheduling inspector will further inspect the evaluation results to determine whether the plan meets the established standards and requirements. If the plan meets all standards and requirements, it is considered qualified; if the plan does not meet any one or more standards and requirements, it is considered unqualified, and then the plans with excellent performance are screened out to form a logistics resource scheduling variation optimization space with high feasibility and practicality; finally, the plans in the logistics resource scheduling variation optimization space are added to the logistics resource scheduling second space, thereby expanding the original plan set, that is, obtaining the logistics resource scheduling third space, which includes more logistics resource scheduling plans that have performed well after evaluation and inspection, which not only have higher feasibility and practicality, but also perform well in all aspects, thereby realizing the optimization of logistics resource scheduling plans and improving logistics efficiency and service quality.

[0041] Furthermore, step S410 also includes step S411, wherein the logistics scheduling variation constraint rule includes the logistics scheduling variation basic quantity; step S412, extracting the nth logistics resource scheduling plan in the second space of the logistics resource scheduling, wherein n is a positive integer; step S413, loading the nth logistics scheduling evaluation result corresponding to the nth logistics resource scheduling plan according to the logistics scheduling evaluation inspection channel; step S414, performing variation value evaluation on the nth logistics resource scheduling plan according to the nth logistics scheduling evaluation result to obtain the variation value coefficient of the nth plan; step S415, performing incentive adjustment on the logistics scheduling variation basic quantity according to the nth plan variation value coefficient to generate the nth variation feature quantity, and adding the nth variation feature quantity to the logistics scheduling variation feature distribution.

[0042] Preferably, based on historical data or business needs, the basic number of logistics scheduling variations of the logistics scheduling variation constraint rules is defined to ensure that the mutated plan has a certain degree of innovation and does not deviate too much from reality, and the n-th specific logistics resource scheduling plan is extracted from the second space of logistics resource scheduling, where n is a positive integer, representing the n-th plan in the second space of logistics resource scheduling, which is less than or equal to the total number of logistics resource scheduling plans in the second space of logistics resource scheduling. The logistics scheduling evaluation test channel is used to load and obtain the logistics scheduling evaluation result corresponding to the n-th logistics resource scheduling plan, which may include indicators in multiple aspects such as timeliness, resource utilization, and cargo loss, etc., to comprehensively reflect the performance of the plan; then based on The nth logistics scheduling evaluation result conducts a variation value evaluation on the nth logistics resource scheduling scheme, that is, a comprehensive analysis and comparison of multiple indicators of the evaluation results is conducted to determine the potential value of the scheme in terms of variation, and then the variation value coefficient of the nth scheme is obtained, which is used to quantify the value of the scheme in the variation process; finally, the variation value coefficient of the nth scheme is used to incentivize and adjust the basic quantity of logistics scheduling variation, including increasing or decreasing the basic quantity to reflect the potential value and importance of the scheme in terms of variation, thereby generating the nth variation feature quantity and adding it to the logistics scheduling variation feature distribution. Among them, the variation feature quantity helps to improve the flexibility and innovation of the logistics resource scheduling scheme, thereby improving logistics efficiency and service quality.

[0043] Step S500: Optimizing the logistics resource scheduling optimization strategy by maximizing the logistics scheduling optimization in the third space of the logistics resource scheduling according to the logistics scheduling optimization analyzer.

[0044] Preferably, the logistics scheduling optimality refers to the comprehensive performance of the logistics resource scheduling plan in terms of meeting customer needs, reducing costs, and improving efficiency. The higher the optimality, the better the scheduling plan. Specifically, the third space of logistics resource scheduling after mutation and expansion is used as input and input into the logistics scheduling optimality parser to maximize the logistics scheduling optimality. The logistics scheduling optimality parser is used to comprehensively evaluate the input scheduling plan, including evaluation of transportation cost, transportation time, customer satisfaction, resource utilization, etc., and use the logistics scheduling optimality parsing function to iterate and optimize the scheduling plan multiple times until the optimal solution is found, and then obtain the scheduling plan that can maximize the logistics scheduling optimality. As the final logistics resource scheduling optimization strategy, it contains the optimal scheduling plan, resource allocation, transportation route and other information, so as to achieve the optimization and efficiency of logistics scheduling, improve logistics efficiency and service quality as well as resource utilization.

[0045] Furthermore, step S500 further includes: the logistics scheduling optimality parser includes a logistics scheduling optimality parsing function, and the logistics scheduling optimality parsing function is: ;

[0046] Among them, OLS represents the optimality of logistics scheduling, OLK represents the analytical factor of the optimality of logistics scheduling, OLK>1, G(TES) represents the normalized timeliness of logistics scheduling, TESW represents the timeliness-weight of logistics scheduling, G(LRX) represents the normalized logistics resource utilization, LRXW represents the logistics resource utilization-weight, G(LCX) represents the normalized logistics cargo loss coefficient, and LCXW represents the logistics cargo loss weight.

[0047] Step S600: executing the short-distance logistics task according to the logistics instant handover chain and the logistics resource scheduling optimization strategy.

[0048] Preferably, executing short-distance logistics tasks according to the logistics instant handover chain and logistics resource scheduling optimization strategy means combining efficient instant handover processes and optimized resource scheduling plans for short-distance transportation, and ensuring the smooth and efficient completion of logistics tasks. Specifically, the logistics instant handover chain and logistics resource scheduling optimization strategy are combined to more effectively execute short-distance logistics tasks, including formulating detailed logistics plans according to the logistics instant handover chain and resource scheduling optimization strategy, such as determining transportation routes, resource allocation, handover processes, etc., and then monitoring the status and location information of the goods in real time through advanced logistics information systems. According to actual conditions and changes in demand, the logistics plan is dynamically adjusted to ensure the smooth progress of the task, strengthen communication and collaboration between various links, ensure the accurate transmission of information and the smooth progress of handover, promptly handle possible problems and abnormal situations, ensure the efficient completion of logistics tasks, and thus improve logistics efficiency and service quality, meet customer needs and reduce operating costs.

[0049] In the above, refer to Figure 1 A short distance logistics management method supporting instant delivery according to an embodiment of the present invention is described in detail. Figure 2 A short-distance logistics management system supporting instant delivery according to an embodiment of the present invention is described.

[0050] According to an embodiment of the present invention, a short-distance logistics management system that supports instant handover is used to solve the technical problems of low efficiency in short-distance logistics task scheduling, unreasonable resource allocation, and delayed handover node management in the existing technology, achieving the technical effect of improving task execution efficiency, enhancing management flexibility and intelligence level. Figure 2 As shown, a short-distance logistics management system supporting instant handover includes: an instant handover node identification module 10, a logistics resource joint scheduling module 20, an evaluation and inspection optimization module 30, a mutation and expansion module 40, a scheduling optimization strategy generation module 50, and a short-distance logistics task execution module 60.

[0051] An instant handover node identification module 10 is used to identify instant handover nodes based on short-distance logistics tasks and generate a logistics instant handover chain; a logistics resource joint scheduling module 20 is used to perform multi-node logistics resource joint scheduling for the short-distance logistics tasks based on the logistics instant handover chain and establish a first logistics resource scheduling space; an evaluation, inspection and optimization module 30 is used to introduce a logistics scheduling evaluation and inspection channel to evaluate, inspect and optimize the first logistics resource scheduling space and generate a second logistics resource scheduling space; a mutation and expansion module 40 is used to perform mutation and expansion on the second logistics resource scheduling space according to the logistics scheduling mutation constraint rules to obtain a third logistics resource scheduling space; a scheduling optimization strategy generation module 50 is used to perform logistics scheduling optimal maximization optimization on the third logistics resource scheduling space according to a logistics scheduling optimality analyzer and generate a logistics resource scheduling optimization strategy; a short-distance logistics task execution module 60 is used to execute the short-distance logistics task according to the logistics instant handover chain and the logistics resource scheduling optimization strategy.

[0052] The specific configuration of the logistics resource joint scheduling module 20 will be described in detail below. The logistics resource joint scheduling module 20 further includes: collecting logistics resource information based on the logistics instant handover chain to obtain multiple node logistics resource data sets; organizing the multiple node logistics resource data sets to establish multiple node logistics resource spaces; scheduling logistics resources for the short-distance logistics tasks based on the multiple node logistics resource spaces to obtain multiple node logistics resource scheduling decision sets; and combining multiple node logistics resource scheduling decisions based on the multiple node logistics resource scheduling decision sets to generate the first logistics resource scheduling space.

[0053] The specific configuration of the evaluation, inspection and optimization module 30 will be described in detail below. The evaluation, inspection and optimization module 30 further includes: the logistics scheduling evaluation and inspection channel includes a logistics scheduling evaluator and a logistics scheduling verifier; traversing the first logistics resource scheduling space, extracting the first logistics resource scheduling plan; inputting the first logistics resource scheduling plan into the logistics scheduling evaluator to obtain a first logistics scheduling evaluation result, wherein the logistics scheduling evaluator includes a logistics scheduling timeliness evaluation model, a logistics resource utilization evaluation model and a logistics cargo loss evaluation model; inputting the first logistics scheduling evaluation result into the logistics scheduling verifier to obtain a first logistics scheduling inspection result; when the first logistics scheduling inspection result is unqualified, eliminating the first logistics resource scheduling plan; when the first logistics scheduling inspection result is qualified, adding the first logistics resource scheduling plan to the second logistics resource scheduling space.

[0054] The specific configuration of the evaluation, inspection, and optimization module 30 will be described in detail below. The evaluation, inspection, and optimization module 30 further includes: the logistics scheduling verifier includes a logistics scheduling verification operator, and the logistics scheduling verification operator includes: if the first logistics scheduling evaluation result satisfies the logistics scheduling evaluation constraints, the first logistics scheduling verification result is qualified, wherein the logistics scheduling evaluation constraints include logistics scheduling timeliness constraints, logistics resource utilization constraints, and logistics cargo loss constraints; if the first logistics scheduling evaluation result does not satisfy the logistics scheduling evaluation constraints, the first logistics scheduling verification result is unqualified.

[0055] The specific configuration of the variation expansion module 40 will be described in detail below. The variation expansion module 40 further includes: calculating variation characteristic parameters of the second logistics resource scheduling space according to the logistics scheduling variation constraint rules to obtain a logistics scheduling variation characteristic distribution; mutating the second logistics resource scheduling space according to the logistics scheduling variation characteristic distribution to obtain a logistics resource scheduling variation space; evaluating and testing the logistics resource scheduling variation space according to the logistics scheduling evaluation and testing channel to generate a logistics resource scheduling variation optimization space; and expanding the second logistics resource scheduling space according to the logistics resource scheduling variation optimization space to obtain the logistics resource scheduling third space.

[0056] The specific configuration of the variation expansion module 40 will be described in detail below. The variation expansion module 40 further includes: the logistics scheduling variation constraint rule includes a logistics scheduling variation base quantity; extracting the nth logistics resource scheduling plan within the second space of the logistics resource scheduling, where n is a positive integer; loading the nth logistics scheduling evaluation result corresponding to the nth logistics resource scheduling plan according to the logistics scheduling evaluation verification channel; performing a variation value evaluation on the nth logistics resource scheduling plan according to the nth logistics scheduling evaluation result to obtain the variation value coefficient of the nth plan; performing an incentive adjustment on the logistics scheduling variation base quantity according to the nth plan variation value coefficient to generate an nth variation feature quantity, and adding the nth variation feature quantity to the logistics scheduling variation feature distribution.

[0057] The following will describe in detail the specific configuration of the scheduling optimization strategy generation module 50. The scheduling optimization strategy generation module 50 further includes: the logistics scheduling optimality parser includes a logistics scheduling optimality parsing function, and the logistics scheduling optimality parsing function is: ;

[0058] Among them, OLS represents the optimality of logistics scheduling, OLK represents the analytical factor of the optimality of logistics scheduling, OLK>1, G(TES) represents the normalized timeliness of logistics scheduling, TESW represents the timeliness-weight of logistics scheduling, G(LRX) represents the normalized logistics resource utilization, LRXW represents the logistics resource utilization-weight, G(LCX) represents the normalized logistics cargo loss coefficient, and LCXW represents the logistics cargo loss weight.

[0059] A short-distance logistics management system supporting instant handover provided by an embodiment of the present invention can execute a short-distance logistics management method supporting instant handover provided by any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0060] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other and are not used to limit the scope of protection of the present invention.

[0061] The above specific embodiments do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. A short-distance logistics management method supporting instant delivery, characterized in that: The method comprises: Identify real-time handover nodes based on short-distance logistics tasks and generate real-time logistics handover chains; Perform multi-node logistics resource joint scheduling for the short-distance logistics task based on the logistics instant handover chain, and establish a first logistics resource scheduling space; Introducing a logistics scheduling evaluation and inspection channel to evaluate and inspect the first logistics resource scheduling space and optimize it, thereby generating a second logistics resource scheduling space; Performing mutation and expansion on the second logistics resource scheduling space according to the logistics scheduling mutation constraint rule to obtain a third logistics resource scheduling space; Performing logistics scheduling optimization maximization optimization on the third space of logistics resource scheduling according to the logistics scheduling optimization analyzer to generate a logistics resource scheduling optimization strategy; Execute the short-distance logistics task according to the logistics instant handover chain and the logistics resource scheduling optimization strategy; The logistics scheduling optimality parser includes a logistics scheduling optimality parsing function, and the logistics scheduling optimality parsing function is: ； Among them, OLS represents the optimality of logistics scheduling, OLK represents the analytical factor of the optimality of logistics scheduling, OLK>1, G(TES) represents the normalized timeliness of logistics scheduling, TESW represents the timeliness-weight of logistics scheduling, G(LRX) represents the normalized logistics resource utilization, LRXW represents the logistics resource utilization-weight, G(LCX) represents the normalized logistics cargo loss coefficient, and LCXW represents the logistics cargo loss weight.

2. A short-distance logistics management method supporting instant delivery as claimed in claim 1, characterized in that: The multi-node logistics resource joint scheduling is performed for the short-distance logistics task according to the logistics instant handover chain, and a first logistics resource scheduling space is established, including: Collect logistics resource information according to the logistics instant handover chain to obtain multiple node logistics resource data sets; Arranging the plurality of node logistics resource data sets to establish a plurality of node logistics resource spaces; Performing logistics resource scheduling on the short-distance logistics task according to the multiple node logistics resource spaces to obtain multiple node logistics resource scheduling decision sets; A multi-node logistics resource scheduling decision combination is performed based on the multiple node logistics resource scheduling decision sets to generate the first logistics resource scheduling space.

3. The short-distance logistics management method supporting instant delivery according to claim 1, characterized in that: Introducing a logistics scheduling evaluation and inspection channel to evaluate and inspect the first logistics resource scheduling space and optimize it, generating a second logistics resource scheduling space, including: The logistics scheduling evaluation and inspection channel includes a logistics scheduling evaluator and a logistics scheduling inspector; Traversing the first logistics resource scheduling space and extracting a first logistics resource scheduling plan; Inputting the first logistics resource scheduling plan into the logistics scheduling evaluator to obtain a first logistics scheduling evaluation result, wherein the logistics scheduling evaluator includes a logistics scheduling timeliness evaluation model, a logistics resource utilization evaluation model, and a logistics cargo loss evaluation model; Inputting the first logistics scheduling evaluation result into the logistics scheduling verifier to obtain a first logistics scheduling verification result; When the first logistics scheduling test result is unqualified, eliminating the first logistics resource scheduling plan; When the first logistics scheduling inspection result is qualified, the first logistics resource scheduling plan is added to the second logistics resource scheduling space.

4. A short-distance logistics management method supporting instant delivery as claimed in claim 3, characterized in that: The logistics scheduling checker includes a logistics scheduling check operator, and the logistics scheduling check operator includes: If the first logistics scheduling evaluation result satisfies the logistics scheduling evaluation constraints, the first logistics scheduling inspection result is qualified, wherein the logistics scheduling evaluation constraints include logistics scheduling timeliness constraints, logistics resource utilization constraints, and logistics cargo loss constraints; If the first logistics scheduling evaluation result does not meet the logistics scheduling evaluation constraint, the first logistics scheduling inspection result is unqualified.

5. The short-distance logistics management method supporting instant delivery according to claim 1, characterized in that: The second logistics resource scheduling space is mutated and expanded according to the logistics scheduling variation constraint rule to obtain a third logistics resource scheduling space, including: Calculating variation characteristic parameters of the second logistics resource scheduling space according to the logistics scheduling variation constraint rule to obtain a logistics scheduling variation characteristic distribution; According to the distribution of the variation characteristics of the logistics scheduling, the second space of the logistics resource scheduling is mutated to obtain the variation space of the logistics resource scheduling; The logistics resource scheduling variation space is evaluated and tested according to the logistics scheduling evaluation and testing channel to generate a logistics resource scheduling variation optimization space; The second logistics resource scheduling space is expanded according to the logistics resource scheduling variation optimization space to obtain the third logistics resource scheduling space.

6. A short-distance logistics management method supporting instant delivery as claimed in claim 5, characterized in that: Calculating variation characteristic parameters of the second logistics resource scheduling space according to the logistics scheduling variation constraint rule to obtain a logistics scheduling variation characteristic distribution includes: The logistics scheduling variation constraint rules include logistics scheduling variation basic quantity; Extracting the nth logistics resource scheduling plan in the second logistics resource scheduling space, where n is a positive integer; According to the logistics scheduling evaluation verification channel, the nth logistics scheduling evaluation result corresponding to the nth logistics resource scheduling plan is loaded; Performing a variation value evaluation on the nth logistics resource scheduling plan according to the nth logistics scheduling evaluation result to obtain a variation value coefficient of the nth plan; The logistics scheduling variation base quantity is incentivized and adjusted according to the nth scheme variation value coefficient to generate the nth variation feature quantity, and the nth variation feature quantity is added to the logistics scheduling variation feature distribution.

7. A short-distance logistics management system supporting instant delivery, characterized in that: The system is used to implement the short-distance logistics management method supporting instant delivery as described in any one of claims 1 to 6, and the system includes: Instant handover node identification module, used to identify instant handover nodes based on short-distance logistics tasks and generate logistics instant handover chains; A logistics resource joint scheduling module is used to perform multi-node logistics resource joint scheduling for the short-distance logistics task according to the logistics instant handover chain, and establish a first logistics resource scheduling space; An evaluation, inspection, and optimization module is used to introduce a logistics scheduling evaluation and inspection channel to evaluate, inspect, and optimize the first logistics resource scheduling space to generate a second logistics resource scheduling space; a mutation and expansion module, configured to perform mutation and expansion on the second logistics resource scheduling space according to the logistics scheduling mutation constraint rule to obtain a third logistics resource scheduling space; A scheduling optimization strategy generation module is used to maximize the optimization of the logistics scheduling optimality of the logistics resource scheduling third space according to the logistics scheduling optimality analyzer, and generate a logistics resource scheduling optimal strategy; The short-distance logistics task execution module is used to execute the short-distance logistics task according to the logistics instant handover chain and the logistics resource scheduling optimization strategy.

Images