CN115700671A

CN115700671A - Logistics scheme planning method, device, equipment and medium

Info

Publication number: CN115700671A
Application number: CN202110850457.1A
Authority: CN
Inventors: 戴伟斌; 王振蒙; 高磊; 刘子恒; 陈博晓; 蔡威威; 易骏杰; 张颖芳; 陈麒昌; 侯璇
Original assignee: SF Technology Co Ltd
Current assignee: SF Technology Co Ltd
Priority date: 2021-07-27
Filing date: 2021-07-27
Publication date: 2023-02-07

Abstract

The application provides a logistics scheme planning method, a device, equipment and a medium; the method comprises the following steps: acquiring transportation demand information and site information of each site in a logistics network corresponding to the transportation demand information; inputting the transportation demand information and the site information of each site into a preset logistics planning model to obtain an initial solution; adjusting the transportation demand parameters according to a preset local search strategy, and processing the adjusted transportation demand parameters through a preset logistics planning model to iteratively update the initial solution to obtain an updated solution; if the update solution meets the preset planning condition, acquiring a target transportation demand parameter corresponding to the update solution, and outputting a logistics planning scheme corresponding to the target transportation demand parameter; the logistics planning model is preset in the embodiment of the application and vehicle position limit and cargo capacity processing capacity of each site are considered, so that the total cost of vehicle transportation cost and site processing cost is minimized, and logistics planning schemes corresponding to logistics network lines and vehicle arrangement are more accurate and efficient.

Description

Logistics scheme planning method, device, equipment and medium

Technical Field

The application relates to the field of logistics, in particular to a logistics scheme planning method, a logistics scheme planning device, a logistics scheme planning equipment and a logistics scheme planning medium.

Background

With the rapid development of society, the logistics demand is larger and larger, and the logistics efficiency and the logistics cost are influenced by the logistics network line and vehicle arrangement planning in the logistics scheme.

The logistics scheme planning means that: under the condition that space-time connection relation between fields and transportation requirements of customers in a logistics network are known and the constraint conditions of transportation timeliness limitation, vehicle load limitation and the like are met, a proper transportation path is selected for the transportation requirements and vehicles among the fields are reasonably arranged, so that the total cost including vehicle transportation cost and field cargo quantity processing cost is low. Because the current logistics network is complex and the transportation demand scale is large, a reasonable logistics network line and vehicle arrangement planning scheme is difficult to obtain, how to carry out logistics network line and vehicle arrangement planning, the total cost of vehicle transportation cost and site cargo quantity processing cost is low while the transportation demand is met, and the technical problem to be solved urgently at present is formed.

Disclosure of Invention

The application provides a logistics scheme planning method, a logistics scheme planning device, equipment and a medium, and aims to solve the technical problems that the cost of a planning scheme cannot be guaranteed to be the lowest in the existing logistics scheme planning, the logistics scheme planning is complex, and real-time performance and flexibility are unavailable.

In one aspect, the present application provides a logistics plan planning method, including:

acquiring transportation demand information and site information of each site in a logistics network corresponding to the transportation demand information;

inputting the transportation demand information and the site information of each site into a preset logistics planning model to obtain an initial solution;

adjusting the transportation demand parameters according to a preset local search strategy, and processing the adjusted transportation demand parameters through the preset logistics planning model to iteratively update the initial solution to obtain an updated solution;

and if the updated solution meets the preset planning condition, acquiring a logistics planning scheme corresponding to the updated solution.

In some embodiments of the present application, before the transportation demand information and the site information of each of the sites are input into a preset logistics planning model and an initial solution is obtained, the method includes:

receiving a model construction instruction, and acquiring site information of each site in a logistics network and a plurality of transportation demand information in a historical time period;

generating a site path according to site information of each site in the logistics network and the plurality of transportation demand information;

generating a shift route according to the site route, the site information of each site and the vehicle driving time among the sites;

screening each shift path according to the transportation timeliness in each piece of transportation demand information to obtain a feasible path set;

and constructing a preset logistics planning model according to the transportation proportion of each path in the feasible path set, the distribution information of vehicle clamping positions in each field shift and the arrangement information of vehicles between each pair of field shifts.

In some embodiments of the present application, the constructing a preset logistics planning model according to the transportation proportion of each route in the feasible route set, the allocation information of vehicle clamps in each site shift, and the arrangement information of vehicles between each pair of site shifts includes:

setting constraint conditions according to the transportation proportion of each path in the feasible path set, the distribution information of vehicle screens in each field shift and the arrangement information of vehicles between each field shift;

and setting an objective function according to the constraint condition, the vehicle transportation cost and the site transfer processing cost, and packaging the constraint condition and the objective function to obtain a preset logistics planning model, wherein the objective function is a function of the transportation demand information dependent variable, the vehicle transportation cost and the site processing cost.

In some embodiments of the present application, the inputting the transportation demand information and the site information of each of the sites into a preset logistics planning model to obtain an initial solution includes:

inputting the transportation demand information and the site information of each site into a preset logistics planning model, and analyzing the transportation amount, the transportation time, the transportation initial address and the transportation destination address in the transportation demand information through the preset logistics planning model;

configuring transportation demand parameters for each transportation demand parameter in the preset logistics planning model according to the transportation amount, the transportation time, the transportation initial address and the transportation destination address;

and inputting the transportation demand parameters of the transportation demand parameters into a preset logistics planning model to obtain an initial solution.

In an embodiment of the present application, the adjusting the transportation demand parameter according to a preset local search strategy, and processing the adjusted transportation demand parameter through the preset logistics planning model to iteratively update the initial solution to obtain an updated solution includes:

adjusting the transportation demand parameters of the transportation demand parameters in the transportation demand information according to a preset local search strategy to obtain the adjusted transportation demand parameters;

inputting the adjusted transportation demand parameters into a preset logistics planning model, and calculating vehicle transportation cost and site processing cost according to the adjusted transportation demand parameters through the preset logistics planning model to obtain a local optimal solution;

and updating the initial solution according to the local optimal solution to obtain an updated solution.

In an embodiment of the application, after the transportation demand parameter is adjusted according to a preset local search strategy and the adjusted transportation demand parameter is processed by the preset logistics planning model to iteratively update the initial solution to obtain an updated solution, the method includes:

acquiring iteration times and/or iteration time of iterative updating, and acquiring preset times and preset duration corresponding to a preset logistics planning model;

if the iteration times are greater than the preset times and/or if the iteration time is greater than the preset duration, judging that the updating solution meets the preset planning condition;

and if the iteration times are less than or equal to the preset times and/or if the iteration time is less than or equal to the preset duration, judging that the updating solution does not accord with the preset planning condition.

In an embodiment of the present application, after adjusting the transportation demand parameter according to a preset local search strategy and processing the adjusted transportation demand parameter through the preset logistics planning model to iteratively update the initial solution to obtain an updated solution, the method includes:

if the updated solution does not meet the preset planning condition, acquiring each local optimal solution of the historical iteration;

adjusting the preset local search strategy according to the variation trend of each local optimal solution to obtain an updated local search strategy;

adjusting corresponding transportation demand parameters in the transportation demand information according to the updated local search strategy;

and inputting the adjusted transportation demand parameters into a preset logistics planning model to obtain an updated solution.

In an embodiment of the present application, if the updated solution meets a preset planning condition, acquiring a logistics planning scheme corresponding to the updated solution includes:

if the updated solution meets the preset planning condition, obtaining the local optimal solution of each iteration;

and combining the local optimal solutions to form a minimum update solution, acquiring a target transportation demand parameter corresponding to the minimum update solution, logistics route information and vehicle arrangement information corresponding to the target transportation demand parameter, and outputting the logistics route information and the vehicle arrangement information as a logistics planning scheme.

In the embodiment of the application, the acquiring of the transportation demand information, and the transportation demand information corresponding to the site information of each site in the logistics network, includes:

acquiring transportation demand information, and extracting a starting address, time information and destination address information in the transportation demand information;

determining a logistics network according to the starting address, the time information and the destination address information;

inquiring a preset site database, and acquiring site information of each site in the logistics network, wherein the site information comprises site vehicle clamping information, site address information, site shift information and available vehicle information between site shifts.

In another aspect, the present application provides a logistics plan planning apparatus, including:

the system comprises an acquisition module, a storage module and a display module, wherein the acquisition module is used for acquiring transportation demand information and site information of each site in a logistics network corresponding to the transportation demand information;

the planning module is used for inputting the transportation demand information and the site information of each site into a preset logistics planning model to obtain an initial solution;

the updating module is used for adjusting the transportation demand parameters according to a preset local search strategy, and processing the adjusted transportation demand parameters through the preset logistics planning model to update the initial solution in an iterative manner to obtain an updated solution;

and the output module is used for acquiring the logistics planning scheme corresponding to the updating solution if the updating solution meets the preset planning condition.

On the other hand, the present application further provides a logistics scheme planning apparatus, including:

one or more processors;

a 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 plan planning method.

In another aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is loaded by a processor to execute the steps in the logistics plan planning method.

According to the technical scheme, transportation demand information is obtained, and the transportation demand information corresponds to site information of each site in a logistics network; inputting the transportation demand information and the site information of each site into a preset logistics planning model, analyzing the transportation demand information and the site information of each site through the preset logistics planning model, and setting transportation demand parameters to obtain an initial solution; in this way, the preset logistics planning model considers the vehicle position limit and the cargo capacity processing capacity of each site, so that an initial solution corresponding to the total cost of the vehicle transportation cost and the site processing cost is obtained; then adjusting transportation demand parameters according to transportation demand information and site information of each site according to a preset local search strategy to realize partial parameter updating, and further processing the adjusted transportation demand parameters through the preset logistics planning model to iteratively update the initial solution to obtain an updated solution; if the updated solution meets the preset planning condition, acquiring a logistics planning scheme corresponding to the updated solution; and according to a preset local search strategy, partially iteratively updating the solution corresponding to the logistics scheme, so that the calculation amount of planning is small, and the real-time performance and flexibility of the logistics scheme planning are ensured.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1 is a schematic view of a scenario of a logistics scenario planning method provided in an embodiment of the present application;

fig. 2 is a schematic flow chart of an embodiment of pre-constructing a preset logistics planning model in the logistics scheme planning method in the embodiment of the application;

FIG. 3 is a schematic flow diagram of an embodiment of a logistics plan planning method provided in an embodiment of the present application;

fig. 4 is a schematic flow chart of an embodiment of updating a logistics plan in a logistics plan planning method provided in an embodiment of the present application;

fig. 5 is a schematic flowchart of an embodiment of synchronous updating of a local search strategy and a planning scheme in the logistics scheme planning method provided in the embodiment of the application;

fig. 6 is a schematic flow chart of update solution determination in the logistics plan planning method provided in the embodiment of the present application;

fig. 7 is a schematic structural diagram of an embodiment of a logistics scheme planning apparatus provided in an embodiment of the present application;

fig. 8 is a schematic structural diagram of an embodiment of a logistics scheme planning apparatus provided in an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any inventive step, are within the scope of the present invention.

In this application, the word "exemplary" is used to mean "serving as an example, instance, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is presented to enable any person skilled in the art to make and use the invention. In the following description, details are set forth for the purpose of explanation. It will be apparent to one of ordinary skill in the art that the present invention may be practiced without these specific details. In other instances, well-known structures and processes are not shown in detail to avoid obscuring the description of the invention with unnecessary detail. Thus, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.

The embodiments of the present application provide a method, an apparatus, a device, and a medium for planning a logistics plan, which are described in detail below.

The logistics scheme planning method in the embodiment of the invention is applied to a logistics scheme planning device, the logistics scheme planning device is arranged on logistics scheme planning equipment, the logistics scheme planning equipment is provided with 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 are configured to be executed by the processors to realize the logistics scheme planning method; the logistics plan planning device can be a mobile terminal, such as a mobile phone, a tablet computer or a camera.

As shown in fig. 1, fig. 1 is a scene schematic diagram of a logistics scheme planning method according to an embodiment of the present application, where a logistics scheme planning scene includes a logistics scheme planning device 100 (a logistics scheme planning apparatus is integrated in the logistics scheme planning device 100), and a computer-readable storage medium corresponding to a logistics scheme plan is operated in the logistics scheme planning device 100 to execute a step of the logistics scheme planning.

It should be understood that the logistics scheme planning device in the scenario of the logistics scheme planning shown in fig. 1, or the device included in the logistics scheme planning device, does not limit the embodiment of the present invention, that is, the number of devices and the type of devices included in the scenario of the logistics scheme planning, or the number of devices and the type of devices included in each device do not affect the overall implementation of the technical scheme in the embodiment of the present invention, and all of them can be calculated as equivalent replacements or derivatives of the technical scheme claimed in the embodiment of the present invention.

The logistics scheme planning equipment 100 in the embodiment of the invention is mainly used for: acquiring transportation demand information and site information of each site in a logistics network corresponding to the transportation demand information; inputting the transportation demand information and the site information of each site into a preset logistics planning model to obtain an initial solution; the preset logistics planning model analyzes the transportation demand information and the site information of each site to set transportation demand parameters, and calculates vehicle transportation cost and site processing cost according to the transportation demand parameters to obtain an initial solution; adjusting the transportation demand parameters according to a preset local search strategy, and processing the adjusted transportation demand parameters through the preset logistics planning model to iteratively update the initial solution to obtain an updated solution; and if the updated solution meets the preset planning condition, acquiring a logistics planning scheme corresponding to the updated solution.

The logistics scheme planning apparatus 100 in the embodiment of the present invention may be an independent logistics scheme planning apparatus, or a logistics scheme planning apparatus network or a logistics scheme planning apparatus cluster composed of the logistics scheme planning apparatuses, for example, the logistics scheme planning apparatus 100 described in the embodiment of the present invention includes, but is not limited to, a computer, a network host, a single network logistics scheme planning apparatus, a plurality of network logistics scheme planning apparatus sets, or a cloud logistics scheme planning apparatus composed of a plurality of logistics scheme planning apparatuses. The cloud logistics scheme planning device is composed of a large number of computers based on cloud computing (cloud computing) or network logistics scheme planning devices.

Those skilled in the art can understand that the application environment shown in fig. 1 is only one application scenario related to the present embodiment, and does not constitute a limitation on the application scenario of the present embodiment, and that other application environments may further include more or less logistics plan devices than those shown in fig. 1, or a network connection relationship of the logistics plan devices, for example, only 1 logistics plan device is shown in fig. 1, and it can be understood that the scenario of the logistics plan may further include one or more other logistics plan devices, which is not limited herein; the logistics plan planning apparatus 100 may further include a memory for storing data, for example, site information and the like.

In addition, in the scenario of the logistics scheme planning, the logistics scheme planning apparatus 100 may be provided with a display device, or the logistics scheme planning apparatus 100 is not provided with a display device in communication connection with an external display device 200, and the display device 200 is used for outputting a result of the logistics scheme planning method executed by the logistics scheme planning apparatus. The logistics scheme planning apparatus 100 may access a background database 300 (the background database may be in a local memory of the logistics scheme planning apparatus, and may also be set in the cloud), and the background database 300 stores information related to the logistics scheme planning.

It should be noted that the scene schematic diagram of the logistics scheme planning method shown in fig. 1 is only an example, and the scene of the logistics scheme planning described in the embodiment of the present invention is for more clearly illustrating the technical scheme of the embodiment of the present invention, and does not constitute a limitation on the technical scheme provided in the embodiment of the present invention.

The logistics scheme planning method in this embodiment is applied to a logistics scheme planning device, the type of the logistics scheme planning device is not particularly limited, for example, the logistics scheme planning device may be a terminal or a server, the server is taken as an example in this embodiment for explanation, a logistics planning model is preset in the server, the preset logistics planning model refers to a calculation model formed by summarizing a large amount of logistics network lines and vehicle arrangement information in advance, and the preset logistics planning model may select a suitable path according to each transportation demand to optimize the total cost on the premise of meeting the transportation demand.

Vehicle position clamping constraint, cargo capacity handling capacity constraint and the like of a site are considered in the preset logistics planning model. For example, the sum of the vehicle screens allocated to each field shift cannot exceed the number of screens owned by the field, the vehicles can only be operated after the screens are allocated to each field shift in the flow direction, and the daily cargo capacity of each field cannot exceed the processing capacity of each field. The server generates and screens feasible paths for each transportation demand according to the constraint conditions, each transportation demand is met within the time limit, and the server summarizes information of each path to preset a logistics planning model.

As shown in fig. 2, fig. 2 is a schematic flow chart of an embodiment of pre-constructing a preset logistics planning model in the logistics plan planning method in the embodiment of the present application. The method for planning the logistics scheme in the embodiment comprises the steps of constructing a preset logistics planning model, and comprises the following steps:

and 201, receiving a model building instruction, and acquiring site information of each site in the logistics network and a plurality of transportation demand information in a historical time period.

The server receives a model building instruction, where a triggering manner of the model building instruction is not specifically limited, that is, a user may manually trigger the model building instruction, or the server automatically triggers the model building instruction, and after the server receives the model building instruction, the server obtains a model training sample, where the model training sample in this embodiment includes: the method comprises the steps of obtaining site information of each site in a logistics network and a plurality of transportation demand information in historical time periods.

The site information comprises site identification, site addresses, vehicle clamping distribution in the site, site shift arrangement and the like; the transportation demand information refers to the information of transportation demands of different cargoes with different starting addresses and destination addresses and different time limits, and the transportation demand information comprises a plurality of transportation demands of historical time periods, such as a plurality of transportation demands of the past month of the transportation demands.

And 202, generating a site path according to the site information of each site in the logistics network and the plurality of transportation demand information.

The server generates a site path according to site information and a plurality of transportation demand information of each site in the logistics network, for example, the server acquires a start address, time information and destination address information in each transportation demand information, the server determines the site between the start address, the time information and the destination address information to acquire the site information of each site, and the server traces back from the start address to the destination address along each site to obtain the site path formed between the start position and the destination position.

And 203, generating a shift route according to the site route, the site information of each site and the vehicle driving time among the sites.

And 204, screening each shift path according to the transportation timeliness in each piece of transportation demand information to obtain a feasible path set.

The server sorts the vehicle paths corresponding to each transportation demand according to the site paths, the site information of each site and the vehicle running time among the sites to generate a shift path; the server extracts the transportation timeliness in each piece of transportation demand information, and deletes the route of the shift exceeding the transportation timeliness according to the transportation timeliness to obtain a feasible route set.

And 205, constructing a preset logistics planning model according to the transportation proportion of each path in the feasible path set, the distribution information of the vehicle clamping positions in each field shift and the arrangement information of the vehicles between each pair of field shifts.

The server reasonably sets vehicle shift information of the field according to the transportation proportion of each path in the feasible path set, the vehicle running time between the fields, the distribution information of vehicle clamping positions in each field shift and the arrangement information of each pair of vehicles between each field shift, the server takes the field information and the transportation demand information of each field as independent variables, the server takes the vehicle shift information of the field as dependent variables to construct a preset logistics planning model, and the step 205 comprises the following steps:

(1) Setting constraint conditions according to the transportation proportion of each path in the feasible path set, the distribution information of vehicle screens in each field shift and the arrangement information of vehicles between each field shift;

(2) And setting an objective function according to the constraint condition, the vehicle transportation cost and the site transfer processing cost, and packaging the constraint condition and the objective function to obtain a preset logistics planning model, wherein the objective function is a function of an independent variable of the transportation demand information dependent variable of the vehicle transportation cost and the site processing cost.

In this embodiment, the server determines a constraint condition and an objective function according to site information of each site in the logistics network and a plurality of transportation demand information, the server encapsulates the constraint condition and the objective function to form a preset logistics planning model, and the preset logistics planning model is constructed in this embodiment, so that efficient and flexible logistics scheme planning is realized through the preset logistics planning model.

As shown in fig. 3, fig. 3 is a schematic flow chart of an embodiment of a logistics scheme planning method in an embodiment of the present application, where the logistics scheme planning method includes:

301, acquiring transportation demand information and site information of each site in the logistics network corresponding to the transportation demand information.

When the server receives a logistics scheme planning instruction, the server acquires transportation demand information, wherein the transportation demand information comprises transportation volume, transportation initial address and time information, destination address information, transportation time and the like, the server determines a logistics network related to transportation according to the transportation demand information, for example, the transportation demand information is that xxx products are transported from Liaoning Dalian to Jilin Changchun, and the transportation network determined by the server is in the northeast region.

Specifically, step 301 in this embodiment includes:

(1) Acquiring transportation demand information, and extracting a starting address, time information and destination address information in the transportation demand information;

(2) Determining a logistics network according to the starting address, the time information and the destination address information;

(3) And inquiring a preset site database, and acquiring site information of each site in the logistics network, wherein the site information comprises site vehicle position clamping information, site address information, site shift information and available vehicle information between site shifts.

The server acquires the transportation demand information, and extracts a starting address, time information and destination address information in the transportation demand information; the server determines a logistics network according to the initial address, the time information and the destination address information; the server inquires a preset site database, and site information of different sites is stored in the preset site database, wherein the site information comprises site vehicle clamping position information, site address information, site shift information and available vehicle information among site shifts; after the server determines the logistics network, the server acquires the site information of each site in the logistics network, which is stored in a preset site database.

And 302, inputting the transportation demand information and the site information of each site into a preset logistics planning model to obtain an initial solution.

The server sets transportation demand parameters according to freight volume in the transportation demand information, freight time and vacant positions in the site information of each site through a preset logistics planning model, the preset logistics planning model calculates vehicle transportation cost and site processing cost according to the transportation demand parameters to obtain an initial solution, the mode that the server sets the transportation demand parameters in the embodiment is not specifically limited, for example, the server sets transfer times in the transportation demand parameters to zero times according to the transportation demand information, and the cost when the freight volume in the transportation demand information is directly reached is calculated as the initial solution through the preset logistics planning model.

Specifically, the step of calculating the initial solution by using the preset logistics planning model in this embodiment includes:

(1) Inputting the transportation demand information and the site information of each site into a preset logistics planning model, and analyzing the transportation amount, the transportation time, the transportation initial address and the transportation destination address in the transportation demand information through the preset logistics planning model;

(2) Configuring transportation demand parameters for each transportation demand parameter in the preset logistics planning model according to the transportation amount, the transportation time, the transportation initial address and the transportation destination address;

(3) And inputting the transportation demand parameters of the transportation demand parameters into a preset logistics planning model to obtain an initial solution.

In this embodiment, the server calculates an initial solution through a preset logistics planning model to optimize the initial solution to obtain an updated solution, specifically:

303, adjusting the transportation demand parameter according to a preset local search strategy, and processing the adjusted transportation demand parameter through the preset logistics planning model to iteratively update the initial solution to obtain an updated solution.

The server is preset with a local search strategy, which refers to an adjustment strategy of the transportation requirement parameters, for example, the local search strategy may be set to be a random starting address of vehicle transfer in the transportation process, or a random destination address of vehicle transfer in the transportation process. The method comprises the steps that a server fixes partial transportation demand parameters according to a preset local search strategy, then, partial transportation demand parameters in a preset logistics planning model are adjusted, the server calculates to obtain a local optimal solution according to the adjusted partial transportation demand parameters, the server fuses the local optimal solution and an initial solution to obtain an updated solution, further, the server carries out the steps in an iteration mode, the server takes the updated solution obtained last time as a new initial solution, and the server carries out the iteration mode to obtain the new updated solution.

In this embodiment, the server adopts a local update mode, which enables the server to implement partial update, so that the calculation amount of the server is smaller, and an update solution is conveniently obtained.

Since the server needs to know the end point of the iteration, the operation time can be reduced, and the real-time performance of data processing is ensured, after step 303, the method includes:

(1) Acquiring iteration times and/or iteration time of iterative updating, and acquiring preset times and preset duration corresponding to a preset logistics planning model;

(2) If the iteration times are larger than the preset times and/or if the iteration time is larger than the preset duration, judging that the updating solution meets the preset planning condition;

(3) And if the iteration times are less than or equal to the preset times and/or if the iteration time is less than or equal to the preset duration, judging that the updating solution does not accord with the preset planning condition.

The server obtains iteration times and/or iteration time of iterative updating, and the server obtains preset times and preset duration corresponding to a preset logistics planning model; the server compares the iteration times of the iteration update with the preset times corresponding to the preset logistics planning model, and compares the iteration time of the iteration update with the preset duration corresponding to the preset logistics planning model; if the iteration times are larger than the preset times and/or the iteration time is larger than the preset duration, the server judges that the updating solution meets the preset planning condition; and if the iteration times are less than or equal to the preset times and/or the generation time is less than or equal to the preset duration, the server judges that the updating solution does not meet the preset planning condition.

And if the update solution does not accord with the preset planning condition, the server carries out iterative update until the update solution accords with the preset planning condition.

And 304, if the updated solution meets the preset planning condition, acquiring a logistics planning scheme corresponding to the updated solution.

And if the update solution meets the preset planning condition, the server acquires a target transportation demand parameter corresponding to the update solution, and the server takes the logistics route information and the vehicle arrangement information corresponding to the target transportation demand parameter as a final planning scheme and outputs the final planning scheme.

The logistics planning model is preset in the embodiment of the application, vehicle clamping position limitation and cargo capacity processing capacity of each site are considered, and total cost of vehicle transportation cost and site processing cost is considered, so that logistics scheme planning is more reasonable.

For convenience of understanding, a specific application scenario is given in this embodiment for explanation, for example, the server generates a site path for each transportation demand based on the site network V, then generates a shift path based on the site path by considering the property of each site shift (e.n) and the vehicle travel time between sites, and finally filters the shift path based on the aging of each transportation demand to obtain a feasible path set; the server models the feasible path set, and the model makes decisions on the proportion of each transportation demand transported by each path, the allocation of vehicle screens in each field shift, and the arrangement of vehicles used between each pair of field shifts, aiming at minimizing the total cost (including the total transportation cost of vehicles and the total processing cost of the cargo volume passing through all the fields), and considering the screen limit and the processing capacity limit of each field, and the like.

The model input in the preset logistics planning model in this embodiment includes:

(1) And site information: a set V of sites in the logistics network; a set N of site shifts in the logistics network; a site s (i) corresponding to the site shift i, wherein i belongs to N; maximum capacity handling capacity h of site i _i I is an element of V; loading screens g owned by site i _i I is an element of V; cost f for processing single ticket of field i _i I is an element of V; distance d traveled by vehicle between sites i, j _ij ,i,j∈V；

(2) Vehicle information: a unit distance travel cost c of the vehicle; the maximum load weight q of the vehicle;

(3) Transportation demand information: a set of all transportation needs K; set of all feasible paths P for a transportation demand k _k K is an element of K; volume of tickets G for transport request k _k K is equal to K and the transport weight W _k ,k∈K。

In this embodiment, the server needs to pay attention to the following constraints to complete the above tasks:

the sum of the number of the loading screens distributed to all directions in each field shift i cannot exceed the number g of the screens owned by the corresponding field s (i) _s(i) I.e., formula (2); the vehicle can be operated only after the screens are distributed in the flow direction of each field shift, namely, the formula (3); the goods passing through each site cannot exceed the processing capacity of the site, namely, the formula (4); the sum of the maximum loads of vehicles running in the flow direction of each field shift cannot be less than the total weight of the transportation demand using the flow direction, namely formula (5); each transportation requirement is to be fully satisfied while keeping all the cargo fromIt originates a shift for transport to the destination site, equation (6).

The goal of the pre-set logistics planning model is to minimize the total cost (including vehicle transportation costs, which are related to the number of vehicles traveling in each flow direction, etc., and site handling costs, which are related to the total amount of goods passing through each site. The objective function and constraint conditions are as follows:

wherein the content of the first and second substances,X _ij =0 or 1, i.e. if there is one card allocated to flow j for field shift i, X _ij Otherwise, 0,i belongs to N, and j belongs to N; y is _ij Representing the number of departure of a field shift i to a field shift j, wherein i belongs to N, and j belongs to N; beta is a _kp Representing the proportion of the transport demand k transported using the path p

p∈P _k (ii) a M represents a sufficiently large constant.

In this embodiment, the preset logistics planning model selects one or more routes for each transportation demand, and transports all the quantities of goods from the departure node to the destination node, and each route is end-to-end connected by an edge formed by a pair of yard shifts. Based on the transport weight passed by each edge, the transport cost can be minimized by reasonably distributing the vehicles in consideration of the position-locking constraint of the fields at the two ends of the edge. Each route brings the amount of goods to each site that is passed by, and by selecting an appropriate route for each transportation requirement, the sum of the processing costs of all sites can be minimized. And comprehensively considering the transportation cost and the processing cost, thereby finding an optimal path planning and vehicle arrangement scheme.

Referring to fig. 4, fig. 4 is a schematic flow chart of an embodiment of updating a logistics plan in a logistics plan planning method provided in an embodiment of the present application.

In some embodiments of the present application, in the logistics plan planning method, the transportation demand parameter is updated according to a preset local search strategy, and the following steps are executed by performing planning and updating through a preset logistics planning model:

401, adjusting the transportation demand parameters of the transportation demand parameters in the transportation demand information according to a preset local search strategy, and obtaining adjusted transportation demand parameters.

A preset local search strategy in the server, where the preset local search strategy is a transportation demand parameter adjustment strategy corresponding to the transportation demand information, and for example, the preset local search strategy may be a transportation demand parameter random variation strategy, or a transportation demand parameter partial variation strategy; and the server adjusts the transportation demand parameters of the transportation demand parameters in the transportation demand information according to a preset local search strategy to obtain the adjusted transportation demand parameters.

And 402, inputting the adjusted transportation demand parameters into a preset logistics planning model, and calculating vehicle transportation cost and site processing cost according to the adjusted transportation demand parameters through the preset logistics planning model to obtain a local optimal solution.

And 403, updating the initial solution according to the local optimal solution to obtain an updated solution.

The server inputs the adjusted values of the transportation demand parameters into a preset logistics planning model, the preset logistics planning model stores the values of part of the transportation demand parameters unchanged, and part of logistics network lines and vehicle arrangement information are adjusted according to the adjusted values of the transportation demand parameters to obtain a local optimal solution; and the server replaces part of the initial solution with the local optimal solution to obtain an updated solution. In the embodiment, a mode of updating local transportation demand parameters is adopted, the initial solution is updated, so that the data processing amount is small, and meanwhile, the logistics network line and the vehicle arrangement scheme are quickly updated, so that the logistics scheme is more flexibly planned.

Referring to fig. 5, fig. 5 is a schematic flow chart of an embodiment of synchronous updating of a local search strategy and a planning scheme in a logistics scheme planning method provided in an embodiment of the present application, where the logistics scheme planning method in this embodiment includes the following steps:

and 501, if the updated solution does not meet the preset planning condition, acquiring each local optimal solution of the historical iteration.

If the updated solution does not meet the preset planning condition, the server acquires each local optimal solution of the historical iteration, namely, when the server performs iterative updating, different transportation demand parameters are adjusted, a plurality of local optimal solutions are acquired, and the server acquires the local optimal solution generated by the historical iteration.

502, adjusting the preset local search strategy according to the variation trend of each local optimal solution to obtain an updated local search strategy;

the server adjusts the preset local search strategy according to each local optimal solution, namely, the server determines the variation trend of each local optimal solution, and if each local optimal solution is gradually increased, the local search strategy is not adjusted; if the local optimal solutions are gradually reduced, the local search strategy is reversely adjusted, for example, the server analyzes the local optimal solutions to determine whether the local optimal solutions are reduced, and if the local optimal solutions are not reduced, the server adjusts the local search strategy to obtain an updated local search strategy.

503, adjusting each transportation demand parameter corresponding to the transportation demand information according to the updated local search strategy.

And 504, inputting the adjusted transportation demand parameters into a preset logistics planning model to obtain an updated solution.

The server adjusts the transportation demand parameters corresponding to the transportation demand information according to the updated local search strategy, inputs the adjusted values to the preset logistics planning model to obtain an updated solution, and in this embodiment, the local search strategy can be synchronously adjusted according to the change rule of the local optimal solution, so that the server can obtain the logistics planning scheme of the logistics network line and the vehicle arrangement at the fastest speed with the least number of iterations.

Referring to fig. 6, fig. 6 is a schematic flow chart of update solution determination in the logistics plan method provided in the embodiment of the present application, and the update solution determination steps in the logistics plan method in the embodiment are as follows:

601, if the updated solution meets the preset planning condition, obtaining the local optimal solution of each iteration;

602, combining the local optimal solutions to form a minimum update solution, and acquiring a target transportation demand parameter corresponding to the minimum update solution;

603, obtaining logistics line information and vehicle arrangement information corresponding to the target transportation demand parameter, and outputting the logistics line information and the vehicle arrangement information as a logistics planning scheme.

The server judges that the updated solution meets the preset planning condition, and then local optimal solutions of each iteration are obtained; the server combines the local optimal solutions to form a minimum update solution, and the server acquires a target transportation demand parameter corresponding to the minimum update solution; the server acquires logistics route information and vehicle arrangement information corresponding to the target transportation demand parameters, and the server uses the logistics route information and the vehicle arrangement information as a minimum update solution to obtain a corresponding logistics planning scheme. In the embodiment, the server can combine local optimal solutions formed by multiple local searches to obtain an optimal solution, so that vehicle transportation cost and site cargo quantity processing cost corresponding to a scheme obtained by logistics scheme planning are the lowest, and meanwhile, the calculated quantity is the smallest.

In order to better implement the logistics scheme planning method in the embodiment of the application, a logistics scheme planning device is further provided in the embodiment of the application on the basis of the logistics scheme planning method.

As shown in fig. 7, fig. 7 is a schematic structural diagram of an embodiment of the logistics plan planning apparatus; the logistics scheme planning device comprises:

an obtaining module 701, configured to obtain transportation demand information and site information of each site in a logistics network corresponding to the transportation demand information, where the preset logistics planning model analyzes the transportation demand information and the site information of each site to set a transportation demand parameter, and calculates a vehicle transportation cost and a site processing cost according to the transportation demand parameter to obtain an initial solution;

a planning module 702, configured to input the transportation demand information and site information of each site into a preset logistics planning model to obtain an initial solution;

an updating module 703, configured to adjust the transportation demand parameter according to a preset local search strategy, and process the adjusted transportation demand parameter through the preset logistics planning model to iteratively update the initial solution to obtain an updated solution;

an output module 704, configured to obtain a logistics planning scheme corresponding to the update solution if the update solution meets a preset planning condition.

In some embodiments of the present application, the logistics plan planning apparatus includes:

generating a shift route according to the site route, the site information of each site and the vehicle running time among the sites;

In some embodiments of the present application, the logistics plan planning apparatus executes the constructing of a preset logistics planning model according to the transportation proportion of each path in the feasible path set, the allocation information of vehicle screens in each field shift, and the arrangement information of vehicles between each pair of field shifts, including:

and setting an objective function according to the constraint condition and the transportation cost of each path, and packaging the constraint condition and the objective function to obtain a preset logistics planning model, wherein the objective function is a function of the independent variable of the transportation demand information dependent variable of the vehicle transportation cost and the site processing cost.

In some embodiments of the present application, the planning module 702 includes:

inputting the transportation demand information and site information of each site into a preset logistics planning model, and analyzing the transportation amount, the transportation time, the transportation initial address and the transportation destination address in the transportation demand information through the preset logistics planning model;

In some embodiments of the present application, the update module 703 includes:

and if the iteration times are less than or equal to the preset times and/or the iteration time is less than or equal to the preset duration, judging that the updating solution does not accord with the preset planning condition.

adjusting each transportation demand parameter corresponding to the transportation demand information according to the updated local search strategy;

In some embodiments of the present application, the output module 704 includes:

In some embodiments of the present application, the obtaining module 701 includes:

In the embodiment, a logistics scheme planning device acquires transportation demand information and site information of each site in a logistics network corresponding to the transportation demand information; inputting the transportation demand information and the site information of each site into a preset logistics planning model to obtain an initial solution; adjusting the transportation demand parameters according to a preset local search strategy, and processing the adjusted transportation demand parameters through the preset logistics planning model to iteratively update the initial solution to obtain an updated solution; if the updated solution meets the preset planning condition, acquiring a logistics planning scheme corresponding to the updated solution; the logistics planning model is preset in the embodiment of the application, vehicle clamping limitation and cargo capacity processing capacity of each site are considered, total cost of vehicle transportation cost and site processing cost is considered, the logistics scheme planning is more reasonable, meanwhile, the technical scheme in the embodiment updates solutions corresponding to the logistics scheme planning scheme in a partial iteration mode according to a preset local search strategy, the calculation amount of planning is small, and meanwhile, the logistics scheme planning is guaranteed not to have real-time performance and flexibility.

An embodiment of the present invention further provides logistics scheme planning equipment, and as shown in fig. 8, a schematic structural diagram of the logistics scheme planning equipment according to the embodiment of the present invention is shown.

The logistics scheme planning equipment integrates any one logistics scheme planning device provided by the embodiment of the invention, and comprises:

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 processor for performing the steps of the logistics plan planning method described in any of the above logistics plan planning method embodiments.

Specifically, the method comprises the following steps: the logistics plan planning apparatus can include components such as a processor 801 of one or more processing cores, a memory 802 of one or more computer-readable storage media, a power supply 803, and an input unit 804. Those skilled in the art will appreciate that the configuration of the logistics plan planning apparatus shown in fig. 8 does not constitute a limitation of the logistics plan planning apparatus and can include more or fewer components than shown, or some components in combination, or a different arrangement of components. Wherein:

the processor 801 is a control center of the logistics plan planning apparatus, connects various parts of the whole logistics plan planning apparatus by using various interfaces and lines, and executes various functions and processing data of the logistics plan planning apparatus by running or executing software programs and/or modules stored in the memory 802 and calling data stored in the memory 802, thereby performing overall monitoring on the logistics plan planning apparatus. Alternatively, processor 801 may include one or more processing cores; preferably, the processor 801 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 801.

The memory 802 may be used to store software programs and modules, and the processor 801 executes various functional applications and data processing by operating the software programs and modules stored in the memory 802. The memory 802 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created according to the use of the logistics plan planning apparatus, and the like. Further, the memory 802 may include high speed random access memory and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory 802 may also include a memory controller to provide the processor 801 access to the memory 802.

The logistics plan planning apparatus further comprises a power supply 803 for supplying power to each component, and preferably, the power supply 803 may be logically connected to the processor 801 through a power management system, so that functions of managing charging, discharging, power consumption management and the like are realized through the power management system. The power supply 803 may also include one or more dc or ac power sources, recharging systems, power failure detection circuitry, power converters or inverters, power status indicators, and any like components.

The logistics plan planning apparatus may further include an input unit 804, and the input unit 804 may be used to receive input numeric or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

Although not shown, the logistics plan planning apparatus may further include a display unit and the like, which are not described herein. Specifically, in this embodiment, the processor 801 in the logistics plan planning apparatus loads the executable file corresponding to the process of one or more application programs into the memory 802 according to the following instructions, and the processor 801 runs the application programs stored in the memory 802, so as to implement various functions as follows:

It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions, or by instructions controlling associated hardware, which may be stored in a computer-readable storage medium and loaded and executed by a processor.

To this end, an embodiment of the present invention provides a computer-readable storage medium, which may include: read Only Memory (ROM), random Access Memory (RAM), magnetic or optical disks, and the like. The logistics planning system comprises a computer program and a processor, wherein the computer program is stored on the computer program and is loaded by the processor to execute the steps of any one of the logistics planning methods provided by the embodiments of the invention. For example, the computer program may be loaded by a processor to perform the steps of:

In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and parts that are not described in detail in a certain embodiment may refer to the above detailed descriptions of other embodiments, and are not described herein again.

In a specific implementation, each unit or structure may be implemented as an independent entity, or may be combined arbitrarily to be implemented as one or several entities, and the specific implementation of each unit or structure may refer to the foregoing method embodiment, which is not described herein again.

The above operations can be implemented in the foregoing embodiments, and are not described in detail herein.

The logistics scheme planning method provided by the embodiment of the present application is described in detail above, and the principle and the implementation of the present invention are explained in detail herein by applying specific examples, and the description of the above embodiment is only used to help understanding the method and the core idea of the present invention; meanwhile, for those skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims

1. A logistics scheme planning method is characterized by comprising the following steps:

inputting the transportation demand information and the site information of each site into a preset logistics planning model to obtain an initial solution, wherein the preset logistics planning model analyzes the transportation demand information and the site information of each site to set transportation demand parameters, and calculates vehicle transportation cost and site processing cost according to the transportation demand parameters to obtain the initial solution;

and if the updating solution meets the preset planning condition, acquiring a target transportation demand parameter corresponding to the updating solution, and outputting a logistics planning scheme corresponding to the target transportation demand parameter.

2. The method of claim 1, wherein before inputting the transportation demand information and site information of each of the sites into a preset logistics planning model to obtain an initial solution, the method comprises:

3. The method of claim 2, wherein constructing a preset logistics planning model according to the transportation proportion of each route in the feasible route set, the allocation information of vehicle screens in each field shift, and the arrangement information of vehicles between each pair of field shifts comprises:

4. The method of claim 1, wherein the inputting the transportation demand information and the site information of each of the sites into a preset logistics planning model to obtain an initial solution comprises:

and inputting the transportation demand parameters of the transportation demand parameters into a preset logistics planning model to calculate the vehicle transportation cost and the site processing cost, and obtaining an initial solution.

5. The method of claim 1, wherein the adjusting the transportation demand parameter according to a preset local search strategy, and the processing the adjusted transportation demand parameter by the preset logistics planning model to iteratively update the initial solution to obtain an updated solution comprises:

adjusting transportation demand parameters corresponding to the transportation demand parameters in the transportation demand information according to a preset local search strategy to obtain adjusted transportation demand parameters;

6. The method of claim 1, wherein after adjusting the transportation demand parameter according to a preset local search strategy and processing the adjusted transportation demand parameter through the preset logistics planning model to iteratively update the initial solution to obtain an updated solution, the method comprises:

and if the iteration times are less than or equal to the preset times and/or if the iteration time is less than or equal to the preset duration, judging that the updated solution does not meet the preset planning condition, and continuing the iteration solving process.

7. The method of claim 1, wherein after adjusting the transportation demand parameter according to a preset local search strategy and processing the adjusted transportation demand parameter through the preset logistics planning model to iteratively update the initial solution to obtain an updated solution, the method comprises:

8. The method of claim 1, wherein the obtaining the logistics planning scheme corresponding to the updated solution if the updated solution meets a preset planning condition comprises:

combining the local optimal solutions to form a minimum update solution, and acquiring a target transportation demand parameter corresponding to the minimum update solution;

and acquiring logistics line information and vehicle arrangement information corresponding to the target transportation demand parameter, and outputting the logistics line information and the vehicle arrangement information as a logistics planning scheme.

9. The method of claims 1-8, wherein the obtaining of the transportation demand information and the transportation demand information corresponding to site information of each site in the logistics network comprises:

10. A logistics plan planning apparatus, comprising:

11. A logistics plan planning apparatus, comprising:

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 processor to implement the logistics plan planning method of any of claims 1 to 9.

12. A computer-readable storage medium, having stored thereon a computer program which is loaded by a processor to perform the steps of the logistics scheme planning method of any of claims 1 to 9.