CN116882887A

CN116882887A - Material loading strategy generation method and device, electronic equipment and storage medium

Info

Publication number: CN116882887A
Application number: CN202310456500.5A
Authority: CN
Inventors: 麻珺; 邵磊; 管文艳; 王洪大
Original assignee: Casic Simulation Technology Co ltd
Current assignee: Casic Simulation Technology Co ltd
Priority date: 2023-04-25
Filing date: 2023-04-25
Publication date: 2023-10-13

Abstract

The embodiment of the invention relates to a method, a device, electronic equipment and a storage medium for generating a material loading strategy, which comprise the following steps: acquiring a transportation task and a vehicle state; screening out a target vehicle set according to the transportation route information and the vehicle state; determining an available space list according to the target vehicle set; selecting a first space from a plurality of available spaces corresponding to the available space list as a target space; screening loadable target material types and target loading numbers corresponding to each target material type from the materials to be loaded according to the target space, the current number of each material to be loaded and preset constraint conditions; generating a loadable material list according to loadable target material types and target loading quantity corresponding to each target material type; and generating a loading strategy for at least one material to be loaded according to the loadable material list and the available space list.

Description

Material loading strategy generation method and device, electronic equipment and storage medium

Technical Field

The embodiment of the invention relates to the technical field of computers, in particular to a method and a device for generating a material loading strategy, electronic equipment and a storage medium.

Background

Transport capacity measurement is an important component in the transportation task of automobiles. The purpose is to scientifically plan and group the belonged transportation guarantee force by combining the battlefield environment situation and the self transportation resource situation, reasonably allocate the transportation tasks and save the use of transportation resources. In the existing transportation task, required vehicles and loading materials are calculated mainly by virtue of the experience of a commander, and the mode completely depends on the personal experience and capability of the commander, so that the transportation task resources cannot be effectively allocated.

Disclosure of Invention

The application provides a method and a device for generating a material loading strategy, electronic equipment and a storage medium, which are used for solving all or part of the problems in the prior art.

In a first aspect, the present application provides a method for generating a material loading strategy, the method comprising:

acquiring a transportation task and a vehicle state, wherein the transportation task comprises transportation route information, at least one material to be loaded and the current quantity of each material to be loaded;

screening out a target vehicle set according to the transportation route information and the vehicle state;

determining an available space list according to the target vehicle set;

selecting a first space from a plurality of available spaces corresponding to the available space list as a target space, wherein the first space is any one of the available spaces;

Screening loadable target material types and target loading numbers corresponding to each target material type from the materials to be loaded according to the target space, the current number of each material to be loaded and preset constraint conditions;

generating a loadable material list according to loadable target material types and target loading quantity corresponding to each target material type;

and generating a loading strategy for at least one material to be loaded according to the loadable material list and the available space list.

In this way, a target vehicle set is screened out according to the transportation task and the vehicle state, and an available space list is determined according to the target vehicle set; selecting a first space from a plurality of available spaces corresponding to the available space list as a target space, wherein the first space is any one of the available spaces; screening loadable target material types and target loading numbers corresponding to each target material type from the materials to be loaded according to the target space, the current number of each material to be loaded and preset constraint conditions; generating a loadable material list according to loadable target material types and target loading quantity corresponding to each target material type; and generating a loading strategy for at least one material to be loaded according to the loadable material list and the available space list. The method can be used for preparing an effective loading strategy according to the transportation task, the vehicle type, the types and the quantity of materials without depending on personal experience and capability, maximizing the vehicle loading rate, greatly saving transportation resources and improving the transportation resource utilization rate.

With reference to the first aspect, in a first embodiment of the first aspect of the present invention, according to a target space, a current number of each material to be loaded, and a preset constraint condition, selecting a loadable target material type and a target loading number corresponding to each target material type from the materials to be loaded, including:

screening loadable target material types from the materials to be loaded according to the target space and preset constraint conditions, and determining the maximum loading quantity corresponding to each target material type;

comparing the maximum loading quantity of the ith target material category with the current quantity of the ith target material category;

when the maximum loading quantity is larger than or equal to the current quantity, taking the maximum loading quantity as the target loading quantity of the ith target material category;

or alternatively, the process may be performed,

when the maximum loading quantity is smaller than the current quantity, the current quantity is used as the target loading quantity of the ith target material category, wherein the ith target material category is any one of loadable target material categories, and i is a positive integer.

By means of the method, the maximum loading quantity of the target material types is compared with the current quantity, a smaller value is taken as the target loading quantity of the target material types, the situation that the current quantity of the target material types is insufficient for measuring and calculating the maximum loading quantity can be considered, and calculation errors in the loading process are avoided.

With reference to the first aspect or the first embodiment of the first aspect, in a second embodiment of the first aspect of the present invention, generating the loadable material list according to loadable target material types and target loading numbers corresponding to each target material type, includes:

forming a j-th material combination by the j-th material type and the target loading quantity corresponding to the j-th target material, wherein the j-th material type is any one of all target material types, and j is a positive integer;

and generating a loadable material list according to all the material combinations.

By the method, the target loading quantity corresponding to each material is combined into one material group, and similar materials can be combined into a whole for loading, so that statistics and induction processing of the materials are facilitated.

With reference to the first aspect, in a third embodiment of the first aspect of the present invention, generating a loading policy for at least one material to be loaded according to the loadable material list and the available space list specifically includes:

selecting a first loadable material from the loadable material list and loading the first loadable material into the first space;

dividing the remaining space in the first space into at least one subspace;

adding at least one subspace to a head position in the available space list;

With reference to the first aspect or the first embodiment of the first aspect or the third embodiment of the first aspect, in a fourth embodiment of the first aspect of the present invention, the loadable target material category and a target loading number corresponding to each target material category respectively generate a loadable material list, including:

determining the ordering and the corresponding rotation direction of each material in the loadable material list by adopting an optimizing algorithm;

and generating a loadable material list according to the ordering of each material in the loadable material list and the corresponding rotation direction respectively.

In this way, the sorting and rotation direction of each of the loadable materials are determined by the optimizing algorithm, and an optimal loadable material list of the whole available space or the partial available space can be obtained.

With reference to the fourth embodiment of the first aspect, in a fifth embodiment of the first aspect of the present invention, after generating a loading policy for at least one material to be loaded according to the loadable material list and the available space list, the method further includes:

determining consumed materials according to the loading strategy;

And determining the number of loading vehicles required for loading each consumable material according to the consumable material.

According to the method, the consumed goods and materials are determined according to the to-be-loaded vehicles, then the number of the loaded vehicles required by the consumed goods and materials is determined according to the consumed goods and materials, the number of the vehicles required by the consumed goods and materials can be calculated, and transportation planning is carried out together with the to-be-loaded materials.

With reference to the first aspect, in a sixth embodiment of the first aspect of the present invention, when a vehicle in the target vehicle set includes at least two vehicle types, after generating a loading policy for at least one material to be loaded according to the loadable material list and the available space list, the method further includes:

determining a loading rate of each vehicle in the first vehicle type according to the loading strategy;

sequencing the loading rates of all vehicles in the first vehicle type;

selecting a preset number of loading vehicles from all vehicles of the first vehicle type according to the sorting order;

screening at least one candidate vehicle type and the number of vehicles corresponding to the at least one candidate vehicle type from other vehicle types except the first vehicle type by adopting a path reconnection method;

and updating the loading strategy according to the loading materials in the loading vehicle, at least one candidate vehicle type and the number of vehicles corresponding to the at least one candidate vehicle type, wherein the first vehicle type is any one vehicle type of the at least two vehicle types.

In this way, when more than two vehicle types are included, one vehicle type can be loaded first, and then the other vehicle type is loaded by adopting a path reconnection mode, which is beneficial to improving the overall loading rate of the vehicle, thereby improving the utilization rate of vehicle resources.

In a second aspect, the present application provides a material loading policy generating device, including: the device comprises an acquisition module, a screening module, a determination module, a selection module and a generation module;

the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring a transportation task and a vehicle state, wherein the transportation task comprises transportation route information, at least one material to be loaded and the current quantity of each material to be loaded;

the screening module is used for screening out a target vehicle set according to the transportation route information and the vehicle state;

the determining module is used for determining an available space list according to the target vehicle set;

the selecting module is used for selecting a first space from a plurality of available spaces corresponding to the available space list as a target space, wherein the first space is any one of the available spaces;

the screening module is also used for screening loadable target material types and target loading numbers corresponding to each target material type from the materials to be loaded according to the target space, the current number of each material to be loaded and the preset constraint conditions;

The generation module is used for generating a loadable material list according to loadable target material types and target loading quantity corresponding to each target material type; and generating a loading strategy for at least one material to be loaded according to the loadable material list and the available space list.

Optionally, the apparatus further comprises: a processing module and a comparison module;

the processing module is used for screening loadable target material types from the materials to be loaded according to the target space and preset constraint conditions, and determining the maximum loading quantity corresponding to each target material type;

the comparison module is used for comparing the maximum loading quantity of the ith target material category with the current quantity of the ith target material category;

the processing module is further used for taking the maximum loading quantity as the target loading quantity of the ith target material category when the maximum loading quantity is greater than or equal to the current quantity; or when the maximum loading quantity is smaller than the current quantity, the current quantity is taken as the target loading quantity of the ith target material category, wherein the ith target material category is any one of loadable target material categories, and i is a positive integer.

Optionally, the apparatus further comprises: forming a module;

the construction module is used for constructing a j-th material combination by the j-th material type and the target loading quantity corresponding to the j-th target material, wherein the j-th material type is any one of all target material types, and j is a positive integer;

the generation module is also used for generating a loadable material list according to all the material combinations.

Optionally, the apparatus further comprises: dividing the module and adding the module;

the selecting module is also used for selecting a first loadable material from the loadable material list and loading the first loadable material into the first space;

the division module is used for dividing the residual space in the first space into at least one subspace;

a joining module for joining the at least one subspace to a head position in the list of available spaces;

and the generating module is used for generating a loading strategy for at least one material to be loaded according to the loadable material list and the available space list.

Optionally, the apparatus further comprises:

the determining module is also used for determining the ordering and the corresponding rotation direction of each material in the loadable material list by adopting an optimizing algorithm;

the generation module is further used for generating a loadable material list according to the ordering of each material in the loadable material list and the corresponding rotation direction respectively.

Optionally, the apparatus further comprises:

the determining module is also used for determining consumed materials according to the loading strategy; and determining the number of loading vehicles required for loading each consumable material according to the consumable material.

Optionally, the apparatus further comprises: the ordering module and the updating module;

the determining module is further used for determining the loading rate of each vehicle in the first vehicle type according to the loading strategy;

the sequencing module is used for sequencing the loading rates of all vehicles in the first vehicle type;

the selecting module is also used for selecting a preset number of loading vehicles from all vehicles of the first vehicle type according to the sorting order;

the screening module is also used for screening at least one candidate vehicle type and the number of vehicles corresponding to the at least one candidate vehicle type from other vehicle types except the first vehicle type by adopting a path reconnection method;

and the updating module is used for updating the loading strategy according to the loading materials in the loading vehicle, at least one candidate vehicle type and the number of vehicles corresponding to the at least one candidate vehicle type, wherein the first vehicle type is any one of the at least two vehicle types.

In a third aspect, an electronic device is provided, including a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus;

a memory for storing a computer program;

and the processor is used for realizing the steps of the material loading strategy generation method according to any one of the embodiments of the first aspect when executing the program stored in the memory.

In a fourth aspect, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the material loading policy generation method as in any of the embodiments of the first aspect.

Drawings

FIG. 1 is a schematic diagram of a flow chart of operation capacity measurement according to an embodiment of the present invention;

FIG. 2 is a schematic flow chart of a method for generating a loading strategy of materials according to an embodiment of the present invention;

FIG. 3 is a flowchart of a method for determining a target loading number according to an embodiment of the present invention;

FIG. 4 is a schematic flow chart of a material loading method according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of the space division of the materials after loading according to the embodiment of the present invention;

FIG. 6 is a schematic diagram of genotype codes provided by an embodiment of the present invention;

FIG. 7 is a schematic diagram of a material loading strategy generation flow for vehicle adjustment according to the present application;

FIG. 8 is a schematic structural diagram of a device for generating a loading strategy of materials according to an embodiment of the present application;

fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

For the purpose of facilitating an understanding of the embodiments of the present application, reference will now be made to the following description of specific embodiments, taken in conjunction with the accompanying drawings, which are not intended to limit the embodiments of the application.

Aiming at the technical problems mentioned in the background art, the embodiment of the application provides a material loading strategy generation method which can provide a transport capacity measuring function in a transport task, wherein the transport capacity measuring function mainly provides automatic measuring functions such as vehicle demand measuring, replenishment demand measuring, material loading demand measuring and the like. The vehicle demand measurement mainly refers to the measurement of the types and the quantity of command vehicles, transport vehicles and special vehicles required by executing tasks; the replenishment demand measurement is oil filling demand measurement and calculation, and the types and the amounts of oil required for filling various vehicles before the measurement and calculation are carried out; and the loading demand measurement and calculation refers to calculating what type of materials are loaded on each vehicle according to the loading mode of the materials. The method mainly comprises the following steps of calculating and iterating 4 aspects after vehicle screening, vehicle optimization, transportation capacity calculation and manual adjustment: the method is mainly used for automatically measuring and calculating the transport capacity and automatically grouping. The functional architecture is shown in fig. 1, and is mainly divided into the following parts: the method comprises the steps of vehicle primary screening, task allocation under material constraint, vehicle optimization calculation, transport capacity calculation and calculation result correction under manual adjustment. The primary screening of the vehicles is to screen vehicles capable of carrying out transportation tasks according to transportation routes, driving road conditions of the transportation routes and vehicle states in the transportation tasks, task allocation and vehicle optimization calculation under material constraint are achieved by setting an optimization target and constraint conditions, the maximum vehicle loading rate under the minimum vehicles is achieved, and the constraint conditions comprise quality, volume, loading mode and the like, so that the problem of material boxing can be generalized; the transport capacity calculation comprises calculation and calculation of consumed materials, namely supplied materials, and automatic grouping of the materials; the correction of the measurement result under the manual adjustment comprises the adjustment of loading the vehicle by combining a manual mode when the vehicle does not meet the preset requirement.

Based on the above functional architecture, the invention provides a vehicle optimization model, and meanwhile, the vehicle optimization model provided by the invention is based on the following 5 preconditions: 1. all the materials are approximately regarded as cuboid, and the materials which are needed to be carried by personnel do not participate in loading. 2. Good material packaging, and can support bearing and multi-layer loading. 3. The material system is assembled and disassembled, and the condition of halfway loading or unloading is avoided. 4. Only the condition that various materials required by the transportation type vehicles are loaded is considered, other types of vehicles are not used for loading the materials, all types of the transportation type vehicles are consistent, a van is assumed, and the space of the arc-shaped protruding part of the shed roof is not considered. 5. The equipped transport vehicle should be able to load all the supplies.

The vehicle optimization model can be regarded as long as l _i Width is w _i The height is h _i Number n _i Is loaded into a plurality of vehicles with effective volumes V and marked with load weights Q. The number of vehicles which can achieve the final use as much as possible under the condition that certain practical constraints are satisfied is solved.

Consider the following 3 constraints:

1. individual cargo size and weight constraints (C1). The size and weight of the individual cargo must be within the allowable range of the vehicle.

2. Stability constraint (C2). The cargo cannot have a suspended portion.

3. Maximum load, maximum volume constraint (C3) of the vehicle. The total weight, volume of the loaded cargo must not exceed the maximum load, maximum volume of the container itself.

The model can be expressed as follows:

set F= { F _k I k=1, 2, …, K } is the set of target vehicles carrying the material, where K is the number of transport vehicles; let L be the length of the available space of the vehicle, W be the width of the available space of the vehicle, H be the vehicleThe available space is high, V is the effective volume of the available space of the vehicle, and Q is the marked carrying capacity of the available space of the vehicle;

set p= { P _ij |i＝1,2,…,N；j＝1,2,…,n _i The number of the materials is equal to the number of the materials; n is n _i I=1, 2, …, K for the number of i-th supplies; r is the total amount of materials; l (L) _ij Is the length, w of the material _ij Is the width of the materials, h _ij High as material, v _ij For the volume of supplies, m _ij Is the weight of the materials; (P, q, r) is material P _ij The position in the vehicle, wherein p represents the position on the axis corresponding to the vehicle space length of the left front lower vertex of the material, q represents the position on the axis corresponding to the vehicle space width of the left front lower vertex of the material, and r represents the position on the axis corresponding to the vehicle space height of the left front lower vertex of the material; u (u) _ijk Representing material P _ij Whether or not to load the vehicle F _k And (3) internally loading and taking 1, otherwise taking 0.

The vehicle volume utilization of a vehicle can be expressed as:

wherein N is the number of the material types, u _ijk Representing material P _ij Whether or not to load the vehicle F _k In, v _ij The volume of the j-th material in the i-th material is V, and the effective volume of the available space of the vehicle is V.

The load utilization of the vehicle can be expressed as:

wherein N is the number of material types, m _ij The weight of the j-th material in the i-th material, Q is the marking carrying capacity of the available space of the vehicle;

constraints can be expressed as:

1. the total volume of load material is not allowed to exceed the effective volume of the load-bearing vehicle:

2. the total weight of the load material is not allowed to exceed the marking load capacity of the load-bearing vehicle:

3. when materials are loaded and placed in the vehicle, the range of the frame of the vehicle cannot be exceeded:

p∈{x|0≤x≤L-l _ij }

(equation five)

q∈{y|0≤y≤W-w _ij }

(equation six)

r∈{z|0≤z≤H-h _ij }

(equation seven)

Wherein p represents the position of the left front lower vertex of the material on the axis corresponding to the vehicle space length, q represents the position of the left front lower vertex of the material on the axis corresponding to the vehicle space width, r represents the position of the left front lower vertex of the material on the axis corresponding to the vehicle space height, and x, y and z are all intermediate variables and have no special significance.

4. Each piece of material must be loaded into 1 vehicle only, and cannot be repeatedly loaded:

according to the setting, a task vehicle optimization model under the following material constraint conditions is established:

p∈{x|0≤x≤L-l _ij }

q∈{y|0≤y≤W-w _ij }

r∈{z|0≤z≤H-h _ij }

wherein, alpha and beta are constants, and the values are obtained according to experience or actual requirements.

In order to solve the model and realize comprehensive optimization of vehicle volume utilization rate and load utilization rate, the invention provides a material loading strategy generation method, and particularly referring to fig. 2, fig. 2 is a schematic flow chart of a material loading strategy generation method provided by an embodiment of the invention, and the method comprises the following steps:

step 110, a transportation mission and a vehicle status are obtained.

Step 120, screening out the target vehicle set according to the transportation route information and the vehicle state.

Specifically, the transportation task includes transportation route information, at least one material to be loaded, and a current quantity of each material to be loaded. The transportation tasks include transportation route mileage, road conditions of the transportation route, transportation materials, and the like, and the vehicle states include whether the vehicle is in an idle, maintenance, or mission state, and the like.

Aiming at the operation requirements (including operation sites, transportation mileage and the like) of the transportation task, the method excludes some vehicles which cannot participate in the transportation task and cannot meet the standard under the hard condition based on the basic condition information of the vehicles. For example, belonging to a vehicle that is about to be in need of maintenance and is in task.

In an alternative example, for example, a first screening condition is set: the maintenance mileage of the vehicle is calculated according to the selected transportation route, and then is compared with the maintenance mileage of the vehicle, so that the usable vehicle is primarily screened out. The method aims at eliminating the transportation vehicles with insufficient maintenance mileage to complete the total mileage of the transportation route, and is implemented by directly comparing the calculated total mileage with the maintenance mileage of various transportation vehicles, and eliminating vehicles with the maintenance mileage greater than the total mileage in the next screening range if the calculated total mileage is not satisfied.

Setting a second screening condition: the vehicle state, the vehicle which can finish the total mileage of the transportation path through the previous screening can not be dispatched, and the vehicle needs to be further screened according to the current state of the transportation vehicle. Vehicles in idle state are marked 1 and vehicles in non-idle state (e.g., in task, lent, etc.) are marked 0. A logical decision is made to select an idle vehicle labeled 1 for inclusion in the next screening range.

Setting a third screening condition: the driving condition is that according to the driving condition (such as a high altitude area, etc.) of the transportation route, the driving mileage of the vehicle is combined to further screen out suitable vehicles, and transportation vehicles which possibly cannot meet the driving condition under various complex road conditions in the transportation route are removed (such as the high altitude area of the transportation route, and partial types of transportation vehicles cannot participate in calculation due to insufficient power).

The screening conditions are not limited to the three screening conditions listed above, and may be appropriately set according to the transportation task and the actual situation.

Step 130, determining a list of available spaces according to the set of target vehicles.

Specifically, the internal space (length, width, height) of each vehicle in the target vehicle set is determined as an available space, and the internal spaces of all vehicles constitute an available space list.

In an alternative example, vehicle F is selected from a collection of target vehicles, for example _k Vehicle F _k Space (0, 0), L, W, H), and adding to the list of available spaces (i.e., the collection of spaces that can accommodate the material to be loaded)。

And 140, selecting the first space from a plurality of available spaces corresponding to the available space list as a target space.

Specifically, the first space is any one of the available spaces. Any space is selected from the available space list as the current operation space, namely the target space.

In an alternative example, for example, the first element in the list of available spaces (i.e., the first space) is selected as the current operating space, i.e., the target space.

Step 150, screening loadable target material types and target loading numbers corresponding to each target material type from the materials to be loaded according to the target space, the current number of each material to be loaded and the preset constraint conditions.

In particular, the constraint condition may be a constraint of a size, a weight, etc. of the material and a volume and a carrying capacity of the vehicle, for example, a constraint of a size and a weight of the single material, that is, the size and the weight of the single material must be within a range allowed by the vehicle; stability constraint, the material cannot have a suspended part; and maximum load capacity, maximum volume constraint of the vehicle, i.e. the total weight of the loaded material cannot exceed the maximum load capacity of the container itself, and the total volume of the loaded material cannot exceed the maximum volume of the container itself. By setting preset constraint conditions, the loadable target material types and the target loading quantity corresponding to each target material type can be screened from the materials to be loaded according to the current quantity of each material to be loaded and the current operation space, namely the target space.

Optionally, according to the target space, the current number of each material to be loaded and the preset constraint condition, the loadable target material types and the target loading number corresponding to each target material type are screened from the materials to be loaded, which specifically includes the method steps as shown in fig. 3:

step 310, screening loadable target material types from the materials to be loaded according to the target space and the preset constraint conditions, and determining the maximum loading quantity corresponding to each target material type.

Step 320, comparing the maximum loading number of the ith target material category with the current number of the ith target material category.

And 330, when the maximum loading quantity is greater than or equal to the current quantity, taking the maximum loading quantity as the target loading quantity of the ith target material category.

Or alternatively, the process may be performed,

and 340, when the maximum loading quantity is smaller than the current quantity, taking the current quantity as the target loading quantity of the ith target material category.

Specifically, the i-th target material type is any one of loadable target material types, and i is a positive integer. According to the target space, i.e. the current operation space and preset constraint conditions, such as constraint conditions in formulas three to eight, the loadable material types are screened out from the target material types to be loaded, and the maximum loading quantity corresponding to each material type is determined.

The current quantity of the ith material is obtained, the maximum loading quantity of the ith material is compared with the residual quantity of the ith material, and one with a smaller quantity value is selected as the target loading quantity of the material.

In an alternative example, for example, according to the current operation space and the preset constraint condition, the maximum loading number of the a-th material is calculated to be 10, the current number of the a-th material is calculated to be 5, and then the target loading number of the a-th material is calculated to be 5.

In another alternative example, for example, according to the current operation space and the preset constraint condition, the maximum loading number of the B-th material is calculated to be 10, the current number of the B-th material is 20, and the target loading number of the B-th material is calculated to be 10.

By means of the method, the maximum loading quantity of the target material types is compared with the current quantity, a smaller value is taken as the target loading quantity of the target material types, the fact that the current quantity of the target material types does not meet the calculated maximum loading quantity can be considered, and calculation errors in the loading process are avoided.

Step 160, generating a loadable material list according to the loadable target material types and the target loading quantity corresponding to each target material type.

Specifically, loadable target material types and target loading numbers corresponding to each target material type are arranged in sequence to generate a loadable material list.

Optionally, generating the loadable material list according to the loadable target material types and the target loading number corresponding to each target material type, including:

Specifically, in an optional example, the j-th material type and the target loading number corresponding to the j-th target material are combined to form the j-th material combination, and the shape of the material combination can be determined according to the shape of the target operation space.

Step 170, generating a loading strategy for at least one material to be loaded according to the loadable material list and the available space list.

Specifically, a loading strategy for at least one material to be loaded is generated according to the loadable material list and the available space list, wherein the loading strategy comprises the material type, the material quantity, the material placing sequence and direction of each vehicle loading and the like.

Optionally, a loading strategy for at least one material to be loaded is generated according to the loadable material list and the available space list, and the method steps are specifically shown in fig. 4:

step 410, selecting a first loadable material from the loadable material list to load into the first space.

At step 420, the remaining space in the first space is divided into at least one subspace.

At step 430, at least one subspace is added to the head position in the list of available spaces.

Step 440, generating a loading strategy for at least one material to be loaded according to the loadable material list and the available space list.

Specifically, the first loadable material is any loadable material in the loadable material list, the first loadable material is loaded into the first space, then the remaining space of the first space is divided into at least one subspace, the at least one subspace is added to the head position of the available space list in sequence, the available space list is updated, and a loading strategy for at least one material to be loaded is generated according to the loadable material list and the available space list.

In an alternative example, for example, the space division diagram shown in fig. 5 is that the first element of the loadable material list, that is, the first rectangular material group that can be loaded with material, is loaded into the space shown in fig. 5, then the remaining space is divided into three subspaces of a front space, an upper space and a right space, and the three subspaces are respectively stored in the head of the available space list, so as to update the available space list. And continuing to load other material groups of the loadable material list until the available space list or the loadable material list is empty.

In another alternative embodiment, in order to more clearly illustrate the method for generating a material loading policy provided by the embodiment of the present invention, the present invention further provides a flow chart of the method for generating a material loading policy, where it is assumed that vehicle screening has been completed by a screening condition, or that vehicle screening is not required, as shown in fig. 6:

Firstly, reading in vehicle information, adding an available space list, reading in material information, adding a material list to be loaded, judging whether the material list to be loaded is empty according to preset constraint conditions, if the material list to be loaded is not empty, judging whether the available space list is empty, or judging whether the available space list is empty or not, or judging whether the material list to be loaded is empty or not, taking out the first element of the available space list as a current operation space, calculating the loadable material list according to the current operation space and the constraint conditions, selecting the first element of the loadable material list to carry out an integral device, calculating the residual quantity of the material to be loaded, updating the material list to be loaded, storing the residual part of the current operation space as the available space list, and repeating the process, wherein the available space list is empty or the material list to be loaded is empty.

The loading method of the single vehicle obtained by the heuristic search method is that a loading scheme of the single vehicle can completely load the materials is used, but the loading scheme may not be the global or local optimal mode, and the advantages and disadvantages of the method are mainly determined by two factors: 1. ordering of the loadable material list, namely loading sequence of the materials; 2. the rotation direction of each type of material is set. It is therefore desirable to determine these two factors in a single way.

Specifically, a genetic algorithm in the optimizing algorithm can be adopted to determine the optimal solution of the two factors, and the specific process is as follows:

the first step: the coding of the genotype is obtained. Each genotype is a feasible solution sequence, and in the material loading, the content which can be optimized in the loading is divided into two parts, one part is the material loading cis-n, and the other part is the material placing posture. The gene sequence is divided into two parts, the former section represents the order of the loadable material list, the latter section represents the direction of the material placed in the vehicle space when forming a rectangular material group, and one individual in the population is represented by the combination of genes at both ends, as shown in fig. 6.

And a second step of: an fitness function is determined. The fitness function is the evaluation standard of the optimal solution considered by us, the function value is used as the reference value of the natural selection stage, and the larger the value is, the larger the probability that the corresponding genotype is continued. According to the scheme, the space utilization rate and the load utilization rate are used as references, the objective function comprehensively considers the optimization target by combining the two utilization rates, and the loading strategy with the best comprehensive utilization rate is selected by adjusting the space utilization rate and the load utilization rate weight.

And a third step of: a selection operator is determined. The scheme uses a classical roulette selection method to simulate a natural selection process, namely, individuals with each genotype respectively occupy a part of reproduction probabilities in a roulette with total probability of 1 according to fitness function values of the individuals, and individuals with higher fitness have more reproduction opportunities.

Fourth step: setting the crossover rate and the mutation rate. When each round of population is bred to generate new individuals, the crossover is performed in two parts, wherein one part is used for crossing the loading sequence of materials, and a circular crossover operator is used for the part; one part is to cross the rotation direction of the material placement, and the uniform cross operator is used for the part. A new individual is generated through the cross operation of the two parts, and meanwhile, the new individual performs mutation operation according to mutation rate in position, a crossover mutation operator is used for the gene parts in the loading sequence, and a uniform mutation operator is used for the gene parts in the placing posture.

Fifth step: initializing a population with a certain scale, iterating the initial population according to a natural selection process simulated by a selection operator, selecting an individual with the largest fitness function value from each iteration, and obtaining a final optimal individual, namely an optimal boxing sequence through multiple iterations, so that a material list can be loaded.

The following problems may exist with using a single vehicle to load materials: 1. the number of such vehicles is insufficient to complete the resulting boxing scheme; 2. finally, there are situations where the loading rate of one or several vehicles is low. Therefore, the embodiment of the invention also provides a more preferable scheme for solving the problem of loading materials for various vehicle types.

Optionally, the vehicles in the target vehicle set include at least two vehicle types, and after generating a loading strategy for at least one material to be loaded according to the loadable material list and the available space list, the method further includes:

sequencing the loading rates of all vehicles in the first vehicle type;

Specifically, in an alternative example, first, one or more vehicles with the inverse loading rate selected from a single vehicle loading scheme are deleted and the materials loaded therein are removed. Secondly, selecting another or more types of loading vehicles (the vehicle type can be screened according to the weight, the volume and the like of the fetched materials, and the vehicle type can be selected according to actual demands), and updating a loading strategy according to the type of the fetched loading materials, the loading quantity corresponding to each loading material and the selected loading vehicle type and quantity until the number of the vehicles reaches the requirement, the lowest comprehensive loading rate is higher than a certain threshold value or the calculated iteration number reaches the threshold value.

In the process of transporting materials, the consumption materials of the vehicle-mounted personnel and the transport vehicles per se are considered to calculate the loading vehicles required by various consumption materials so as to formulate a complete loading strategy.

Optionally, after generating the loading strategy for the at least one material to be loaded according to the loadable material list and the available space list, the method further comprises:

determining consumed materials according to the loading strategy;

Specifically, in an alternative example, to meet the basic requirements of vehicles and on-board personnel during transportation, consumption of own materials may occur. The self-consumed supplies in the transportation process comprise: fuel consumption in the running process of the automobile, food and drinking water consumption of the personnel on the automobile, tent number required by the personnel on the automobile during long-distance operation on the whole day, and the like.

According to the material loading strategy, M types of vehicles for transporting materials are needed by a road with a calculated transportation path length L, and the number of each type of vehicle is x _i (i=1, 2,) M. The fuel consumption per unit distance of the i type automobile is g _i The total fuel consumption number G can be expressed as:

let the average oil consumption per tank truck be g, the oil quantity that each tank truck can transport be t _g The number N of tank trucks required to be loaded with fuel _g Can be expressed as:

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let p be _ij Representing the number of passengers (including drivers) in the jth vehicle of the ith vehicle, and setting the average food consumed by each passenger as c _f The amount of consumed drinking water is c _w The total consumed food number is F, the total consumed reference water number is W, and the total consumed food and drinking water number FW can be expressed as:

taking food and drinking water as materials, distributing vehicles by using material constraint, and calculating the average quantity t of the food and the drinking water which can be transported by each vehicle _fw The number of people transported on the vehicle is p _fw The number of vehicles N required for loading food and drinking water _fw Can be expressed as:

assuming that one tent is needed per h people, the total number of tents consumed T can be expressed as:

let the average number of people transported on each camping car be p _t The number of tents which can be transported by each tank truck is t _t The number of camping vehicles N needed to load the tent _t Can be expressed as:

if other consumed materials exist, the loading vehicles required by the other consumed materials can be calculated according to the types and the quantity of the materials, and the loading vehicles are specific according to actual conditions.

For the vehicles which are already distributed, if for special reasons, one or a plurality of vehicles cannot transport materials, the method provided by the invention can be used for correcting the loading strategy. And deleting vehicles which cannot be transported from the target vehicle set, and taking the rest vehicles as a new target vehicle set. And then, under the preset constraint condition, carrying out configuration operation on the new target vehicle set again, and returning the results of the reconfigured vehicle condition and the material distribution condition. As shown in fig. 7, when the transport vehicle is adjusted, the transport vehicle list is updated according to the adjusted vehicle, and after the update is completed, the material loading and distribution are performed again, so as to find an optimal distribution scheme and output the optimal material loading scheme.

The foregoing describes other embodiments of the method for generating a material loading policy according to the present application, and is specifically described below.

Fig. 8 is a schematic diagram of a device for generating a loading strategy of materials according to an embodiment of the present application, where the device includes: an acquisition module 801, a screening module 802, a determination module 803, a selection module 804 and a generation module 805;

an obtaining module 801, configured to obtain a transportation task and a vehicle state, where the transportation task includes transportation route information, at least one material to be loaded, and a current number of each material to be loaded;

a screening module 802, configured to screen out a target vehicle set according to the transportation route information and the vehicle status;

a determining module 803, configured to determine an available space list according to the target vehicle set;

a selecting module 804, configured to select a first space from a plurality of available spaces corresponding to the available space list as a target space, where the first space is any one of the plurality of available spaces;

the screening module 802 is further configured to screen loadable target material types and target loading numbers corresponding to each target material type from the materials to be loaded according to the target space, the current number of each material to be loaded and the preset constraint condition;

A generating module 805, configured to generate a loadable material list according to loadable target material types and target loading amounts corresponding to each target material type, respectively; and generating a loading strategy for at least one material to be loaded according to the loadable material list and the available space list.

Optionally, the apparatus further comprises: a processing module 806 and a comparison module 807;

a processing module 806, configured to screen loadable target material types from the materials to be loaded according to the target space and the preset constraint condition, and determine a maximum loading number corresponding to each target material type;

a comparison module 807 for comparing the maximum loading number of the i-th target material category with the current number of the i-th target material category;

the processing module 806 is further configured to, when the maximum loading number is greater than or equal to the current number, use the maximum loading number as the target loading number of the ith target material category; or when the maximum loading quantity is smaller than the current quantity, the current quantity is taken as the target loading quantity of the ith target material category, wherein the ith target material category is any one of loadable target material categories, and i is a positive integer.

Optionally, the apparatus further comprises: a composition module 808;

a forming module 808, configured to form a j-th material category and a target loading number corresponding to the j-th target material, where the j-th material category is any one of all the target material categories, and j is a positive integer;

the generating module 805 is further configured to generate a loadable material list according to all the material combinations.

Optionally, the apparatus further comprises: a partitioning module 809 and a joining module 810;

the selecting module 804 is further configured to select a first loadable material from the loadable material list and load the first space;

a dividing module 809 for dividing the remaining space in the first space into at least one subspace;

a joining module 810 for joining the at least one subspace to a head position in the list of available spaces;

a generating module 805, configured to generate a loading policy for at least one material to be loaded according to the loadable material list and the available space list.

Optionally, the apparatus further comprises:

the determining module 803 is further configured to determine, by using an optimizing algorithm, a ranking and a corresponding rotation direction of each of the loadable materials in the material list;

the generating module 805 is further configured to generate a loadable material list according to the ordering and the corresponding rotation direction of each material in the loadable material list.

Optionally, the apparatus further comprises:

a determining module 803, configured to determine consumption materials according to the loading strategy; and determining the number of loading vehicles required for loading each consumable material according to the consumable material.

Optionally, the apparatus further comprises: a ranking module 811 and an update module 812;

a determining module 803 further configured to determine a loading rate of each vehicle in the first vehicle type according to the loading strategy;

a ranking module 811 for ranking the loading rates of all vehicles in the first vehicle type;

the screening module 802 is further configured to screen at least one candidate vehicle type and a number of vehicles corresponding to the at least one candidate vehicle type from other vehicle types except the first vehicle type by adopting a path reconnection method;

the updating module 812 is configured to update a loading policy according to loading materials in the loading vehicle, at least one candidate vehicle type, and a number of vehicles corresponding to the at least one candidate vehicle type, where the first vehicle type is any one of the at least two vehicle types.

The functions executed by each component in the material loading policy generating device provided in the embodiment of the present invention are described in detail in any of the above method embodiments, so that a detailed description is omitted herein.

According to the material loading strategy generation device provided by the embodiment of the invention, a target vehicle set is screened out according to a transportation task and a vehicle state, and an available space list is determined according to the target vehicle set; selecting a first space from a plurality of available spaces corresponding to the available space list as a target space, wherein the first space is any one of the available spaces; screening loadable target material types and target loading numbers corresponding to each target material type from the materials to be loaded according to the target space, the current number of each material to be loaded and preset constraint conditions; generating a loadable material list according to loadable target material types and target loading quantity corresponding to each target material type; and generating a loading strategy for at least one material to be loaded according to the loadable material list and the available space list. The method can be used for preparing an effective loading strategy according to the transportation task, the vehicle type, the types and the quantity of materials without depending on personal experience and capability, maximizing the vehicle loading rate, greatly saving transportation resources and improving the transportation resource utilization rate.

As shown in fig. 9, an embodiment of the present application provides an electronic device, which includes a processor 111, a communication interface 112, a memory 113, and a communication bus 114, where the processor 111, the communication interface 112, and the memory 113 perform communication with each other through the communication bus 114.

A memory 113 for storing a computer program;

in one embodiment of the present application, the processor 111 is configured to implement the method for generating the material loading policy provided in any one of the foregoing method embodiments when executing the program stored in the memory 113, where the method includes:

determining an available space list according to the target vehicle set;

Optionally, according to the target space, the current number of each material to be loaded and the preset constraint condition, the loadable target material types and the target loading number corresponding to each target material type are screened from the materials to be loaded, including:

or alternatively, the process may be performed,

Optionally, generating a loading strategy for at least one material to be loaded according to the loadable material list and the available space list, which specifically includes:

dividing the remaining space in the first space into at least one subspace;

adding at least one subspace to a head position in the available space list;

Optionally, the loadable target material category and the target loading number corresponding to each target material category respectively generate a loadable material list, including:

determining consumed materials according to the loading strategy;

Optionally, after generating the loading strategy for the at least one material to be loaded according to the loadable material list and the available space list when the vehicles in the target vehicle set include at least two vehicle types, the method further includes:

sequencing the loading rates of all vehicles in the first vehicle type;

The embodiment of the application also provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of the material loading strategy generation method provided in any one of the method embodiments described above.

It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.

The foregoing is merely exemplary of embodiments of the present invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method of generating a material loading strategy, the method comprising:

determining an available space list according to the target vehicle set;

generating a loadable material list according to the loadable target material types and the target loading quantity corresponding to each target material type;

2. The method according to claim 1, wherein the step of screening loadable target material types and target loading numbers corresponding to each target material type from the materials to be loaded according to the target space, the current number of each material to be loaded and a preset constraint condition includes:

When the maximum loading number is greater than or equal to the current number, the maximum loading number is used as the target loading number of the ith target material category;

or alternatively, the process may be performed,

and when the maximum loading quantity is smaller than the current quantity, taking the current quantity as the target loading quantity of the ith target material category, wherein the ith target material category is any one of the loadable target material categories, and i is a positive integer.

3. The method according to claim 1 or 2, wherein the generating the loadable material list according to the loadable target material types and the target loading amounts respectively corresponding to each of the target material types comprises:

and generating the loadable material list according to all the material combinations.

4. The method according to claim 1, wherein the generating a loading strategy for at least one material to be loaded according to the loadable material list and the available space list specifically comprises:

Selecting a first loadable material from the loadable material list and loading the first loadable material into a first space;

dividing the remaining space in the first space into at least one subspace;

adding at least one of said subspaces to a head position in said list of available spaces;

5. The method according to claim 1, 2 or 4, wherein the generating the loadable material list according to the loadable target material types and the target loading numbers respectively corresponding to each of the target material types includes:

6. The method of claim 5, wherein after generating a loading policy for at least one item to be loaded from the loadable list of items and the available space list, the method further comprises:

Determining consumed supplies according to the loading strategy;

7. The method of claim 1, wherein when the vehicles in the set of target vehicles include at least two vehicle types, the method further comprises, after generating a loading strategy for at least one material to be loaded from the loadable list of materials and the available space list:

sequencing the loading rates of all vehicles in the first vehicle type;

and updating the loading strategy according to the loading materials, at least one candidate vehicle type and the vehicle quantity corresponding to at least one candidate vehicle type in the loading vehicle, wherein the first vehicle type is any one vehicle type of the at least two vehicle types.

8. A material loading strategy generation apparatus, the apparatus comprising:

the screening module is further used for screening loadable target material types and target loading numbers corresponding to each target material type from the materials to be loaded according to the target space, the current number of each material to be loaded and preset constraint conditions;

the generation module is used for generating a loadable material list according to the loadable target material types and the target loading quantity respectively corresponding to each target material type; and generating a loading strategy for at least one material to be loaded according to the loadable material list and the available space list.

9. The electronic equipment is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;

the memory is used for storing a computer program;

the processor is configured to implement the steps of the material loading policy generation method according to any one of claims 1 to 7 when executing a program stored in a memory.

10. A computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the steps of the material loading policy generation method of any of claims 1-7.