Multi-vehicle-type electric power material optimized distribution method, system and device and medium

Abstract

The invention is suitable for the technical field of electric power material distribution, and provides a multi-vehicle type electric power material optimized distribution method, system, device and medium, and the method comprises the steps: obtaining a station list comprising a first station and a second station for electric power material distribution and material demands corresponding to different types of stations; traversing all station information in the station list and capacity information of all first vehicles and second vehicles; judging whether the total capacity of all the current to-be-delivered first vehicles can meet the material demand quantity of all the first stations or not; if yes, after the material demand quantity of all the first stations is met, the remaining capacity of all the first vehicles to be delivered is calculated; based on the residual capacity of all the first vehicles to be delivered and the total capacity of all the second vehicles to be delivered currently, whether the material demand quantity of all the second stations can be met or not is judged; and if yes, the distribution paths of all the to-be-distributed first vehicles and all the current to-be-distributed second vehicles are optimized, so that the material distribution efficiency is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power material distribution, and in particular to a method, system, equipment and medium for distributing electric power materials of multiple types. Background Art

[0002] In the process of power material distribution, efficient material distribution is a crucial link. However, existing distribution methods usually rely on a single vehicle model, which is inefficient, costly, and wasteful in resource utilization. At the same time, the planning of distribution routes is usually lacking, resulting in long driving distances and high time consumption, further reducing distribution efficiency. In addition, this single-vehicle distribution method lacks flexibility when facing diversified site requirements, and it is difficult to meet the distribution needs of ordinary sites and small sites at the same time.

[0003] With the continuous development of logistics management and optimization technology, multi-vehicle collaborative scheduling and path optimization methods have made great progress. At present, the optimization methods are mainly based on traditional vehicle path planning algorithms, such as the classic vehicle routing problem (VRP), and intelligent optimization algorithms, such as genetic algorithms and ant colony algorithms. The traditional VRP algorithm is mature, stable and computationally efficient, but it is difficult to find the optimal solution when faced with complex, multi-constrained distribution problems. Intelligent optimization algorithms can find approximate optimal solutions under complex constraints by simulating evolution or group behavior in nature. They have strong adaptability and flexibility, but the amount of calculation is large and the convergence speed is slow, resulting in low optimization efficiency. Summary of the invention

[0004] The embodiments of the present application provide a method, system, device and medium for optimizing the distribution of electric power materials for multiple vehicle types, which are used to solve the problem of low optimization efficiency of distribution of electric power materials.

[0005] A first aspect of an embodiment of the present application provides a method for optimizing the distribution of electric power materials of multiple vehicle types, comprising:

[0006] Obtaining a site list for power material distribution and material demand quantities corresponding to different types of sites, wherein the site list includes a first site and a second site;

[0007] Traversing all site information and capacity information of all vehicle types in the site list, wherein all vehicle types include a first vehicle and a second vehicle;

[0008] Determine whether the total capacity of all first vehicles to be delivered can meet the material demand of all first sites;

[0009] If so, after satisfying the material requirements of all first stations, the remaining capacity of all first vehicles to be delivered is calculated;

[0010] Determining whether the material demand of all the second sites can be met based on the remaining capacity of all the first vehicles to be delivered and the total capacity of all the second vehicles to be delivered;

[0011] If so, the delivery paths of all the first vehicles to be delivered and all the second vehicles currently to be delivered are optimized to obtain a target delivery plan.

[0012] Furthermore, the determining whether the total capacity of all first vehicles to be delivered can meet the material demand of all first sites includes:

[0013] If not, the number of first vehicles is increased, and the total energy of all first vehicles after the increase in the number of the first vehicles is updated until the total capacity of all first vehicles can meet the material demand of all first sites.

[0014] Furthermore, the expression until the total capacity of all first vehicles can meet the material demand of all first sites is as follows:

[0015]

[0016] Where: C s is the total capacity of all first vehicles, n is the number of first stations, d ai is the material demand of the i-th site.

[0017] Furthermore, judging whether the material demand of all second sites can be met based on the remaining capacity of all first vehicles to be delivered and the total capacity of all second vehicles to be delivered currently includes:

[0018] If not, increase the number of second vehicles and update the total capacity of all second vehicles after increasing the number of second vehicles until the remaining capacity of all first vehicles to be delivered and the total capacity of all second vehicles after increasing the number of second vehicles meet the material demand of all second sites.

[0019] Furthermore, the expression for the amount of materials required for all second sites until the remaining capacity of all first vehicles to be delivered and the total capacity of all second vehicles after the number of the second vehicles is increased is as follows:

[0020]

[0021] Where: C l is the total capacity of the second vehicle, is the remaining capacity of all first vehicles, m is the number of second stations, d bj is the material demand of the jth site.

[0022] Furthermore, the optimizing the delivery paths of all the first vehicles to be delivered and all the second vehicles currently to be delivered to obtain a target delivery plan includes:

[0023] The objective function is constructed with the number of all types of vehicles, the routes of all types of vehicles, and the distances between all types of sites as variables and the shortest distribution route of power supplies as the goal;

[0024] Determining constraints of the objective function, wherein the constraints include vehicle capacity constraints and time window constraints;

[0025] The optimization algorithm is used to solve the optimal solution of the objective function to obtain the target distribution plan.

[0026] Furthermore, the expression of the objective function is as follows:

[0027]

[0028] Where: M is the number of vehicles, x ijk Select the variable for the path, d ij is the distance between site i and site j.

[0029] The expressions of the constraints are as follows:

[0030] Vehicle capacity constraints:

[0031]

[0032]

[0033] Among them: A i is the i-th first site, C small is the total capacity of the first vehicle, B j is the jth second site, C large is the total capacity of the second vehicle;

[0034] Time window constraints:

[0035] a i ≤t i ≤ b i ;

[0036] Where: t i is the time when the vehicle arrives at the i-th station, [a i ,b i ] is the time window.

[0037] A second aspect of the embodiment of the present application provides a multi-vehicle power material optimization distribution system, including:

[0038] A site list acquisition unit, used to acquire a site list for power material distribution and material demand quantities corresponding to different types of sites, wherein the site list includes a first site and a second site;

[0039] A site information and capacity information traversal unit, used to traverse all site information and capacity information of all vehicle types in the site list, wherein all vehicle types include a first vehicle and a second vehicle;

[0040] A material demand determination unit for satisfying all first stations, used to determine whether the total capacity of all first vehicles to be delivered can satisfy the material demand of all first stations;

[0041] The remaining capacity calculation unit of the first vehicle is used to calculate the remaining capacity of all the first vehicles to be delivered after the material demands of all the first stations are met, when the total capacity of all the first vehicles to be delivered can meet the material demands of all the first stations;

[0042] A material demand determination unit for satisfying all second sites, configured to determine whether the material demand of all second sites is satisfied based on the remaining capacity of all first vehicles to be delivered and the total capacity of all second vehicles to be delivered;

[0043] The target delivery plan determination unit is used to optimize the delivery routes of all the first vehicles to be delivered and all the second vehicles to be delivered when it is judged that the material demand of all the second sites can be met based on the remaining capacity of all the first vehicles to be delivered and the total capacity of all the second vehicles to be delivered, so as to obtain the target delivery plan.

[0044] A third aspect of the embodiments of the present application provides a computer device, including:

[0045] memories, transceivers, processors, and bus systems;

[0046] Wherein, the memory is used to store programs;

[0047] The processor is used to execute the program in the memory, including executing the multi-vehicle power material optimization distribution method as described in any one of the above items;

[0048] The bus system is used to connect the memory and the processor so that the memory and the processor can communicate with each other.

[0049] A fourth aspect of an embodiment of the present application provides a readable storage medium, including instructions, which, when executed on a computer, enables the computer to execute the multi-vehicle power material optimization distribution method as described in any one of the above items.

[0050] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0051] This application divides the power material distribution site into the first site and the second site, and divides all the vehicles to be distributed into the first vehicle and the second vehicle respectively. After determining that the total capacity of all the first vehicles meets the material demand of all the first sites, and then determining that the remaining capacity of all the first vehicles and the total capacity of all the second vehicles currently to be distributed meet the material demand of all the second sites, the distribution path of all the first vehicles and all the second vehicles currently to be distributed is optimized. This method integrates multi-vehicle scheduling and path optimization technology, realizes efficient distribution to the first site and the second site, and solves the problems of resource waste and inefficiency in the distribution method. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is a schematic diagram of an embodiment of a method for optimizing the distribution of electric power materials of multiple types in the present invention;

[0053] Figure 2 This is a structural diagram of an embodiment of a multi-vehicle power material optimization distribution system in the present invention;

[0054] Figure 3 The figure is a structural block diagram of a computer device in the present invention. DETAILED DESCRIPTION

[0055] The embodiments of the present application provide a method, system, equipment and medium for distributing electric power materials of multiple types, which solve the problems of resource waste and low efficiency in existing distribution methods.

[0056] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein, for example. In addition, the terms "including" and "corresponding to" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0057] Embodiment 1

[0058] The implementation method in this embodiment can be implemented in the system, can be implemented in the server, and can also be implemented in the terminal, and there is no specific limitation. The following will introduce the multi-model power material optimization distribution method in this application from the perspective of the system. Figure 1 , the method provided in this application comprises the following steps:

[0059] S11. Obtain a list of power material distribution sites and material demand corresponding to different types of sites, the site list including a first site and a second site;

[0060] S12. Traverse all site information and capacity information of all vehicle types in the site list, all vehicle types including the first vehicle and the second vehicle;

[0061] The site list for power material distribution includes different types of sites and the material demand corresponding to the sites. Here, the sites for power material distribution are divided into first sites and second sites. The first site is a small site and the second site is an ordinary site.

[0062] Specifically, the first site A set is represented as:

[0063] A={A 1 ,A 2 ,…,A n};

[0064] The second site B set is represented as:

[0065] B={B 1 ,B 2 ,…,B n};

[0066] First Vehicle V small The set is represented as:

[0067] V small = {v 1 ,v 2 ,…,v l};

[0068] Second vehicle V large The set is represented as:

[0069] V large = {v′ 1 ,v′ 2 ,…,v′ k};

[0070] Specifically, all the site information in the site list includes the site type and the material demand corresponding to each site. Two types of vehicles are set here, namely the first vehicle and the second vehicle, where the first vehicle refers to a small car and the second vehicle refers to a large car. The first site (small site) can only be delivered by the first vehicle, and the second site (ordinary site) can be delivered by the first vehicle and / or the second vehicle.

[0071] The material demand of the first station D A It can be expressed as follows:

[0072]

[0073] The material demand of the second station D B It can be expressed as follows:

[0074]

[0075] Where: n is the number of sites at the first site, A i is the material demand of the i-th site; m is the number of sites of the second site, B j is the material demand of the jth site.

[0076] S13. Determine whether the total capacity of all first vehicles currently to be delivered can meet the material demand of all first stations;

[0077] S14. If the total capacity of all first vehicles to be delivered cannot meet the material demand of all first stations, increase the number of first vehicles, and update the total capacity of all first vehicles after the increase in the number of first vehicles, until the total capacity of all first vehicles can meet the material demand of all first stations;

[0078] S15. If the total capacity of all first vehicles to be delivered can meet the material demand of all first sites, then after meeting the material demand of all first sites, the remaining capacity of all first vehicles to be delivered is calculated;

[0079] Specifically, in the process of vehicle dispatch for power material distribution, the first vehicle (small vehicle) list and its corresponding capacity list, and the second vehicle (large vehicle) list and its corresponding capacity list are initialized. According to the demand and type of each site, small vehicles are given priority to deliver to small sites, that is, the first vehicle delivers to the first site, and the demand of each small site and the dispatched vehicles are recorded. Therefore, it is necessary to determine whether the total capacity of all small vehicles to be delivered can meet the material demand of all small sites. If the total capacity of all first vehicles to be delivered cannot meet the material demand of all first sites, the number of first vehicles is increased, and the total energy of all first vehicles after the increase in the number of first vehicles is updated. Let the capacity of the increased first vehicles be C. mew , then redistribute the records, the new total capacity C′ s for:

[0080] C′ s =C s +C mew ;

[0081] Until the total capacity of all first vehicles can meet the material demand of all first sites, the specific expression is as follows:

[0082]

[0083] Where: C s is the total capacity of all first vehicles, n is the number of first stations, d ai is the material demand of the i-th site.

[0084] When C s When the above expression is satisfied, it means that all the first vehicles can be delivered to the first station.

[0085] S16. Determine whether the material demand of all second sites can be met based on the remaining capacity of all first vehicles to be delivered and the total capacity of all second vehicles to be delivered;

[0086] S17. When it is determined that the material demand of all the second sites cannot be met based on the remaining capacity of all the first vehicles to be delivered and the total capacity of all the second vehicles to be delivered, the number of second vehicles is increased, and the total capacity of all the second vehicles after the increase in the number of second vehicles is updated, until the remaining capacity of all the first vehicles to be delivered and the total capacity of all the second vehicles after the increase in the number of second vehicles meet the material demand of all the second sites;

[0087] Specifically, after the material demand of all first stations is met, the remaining capacity of all first vehicles to be delivered is calculated by subtracting the total capacity of all first vehicles to be delivered from the initial total capacity. After meeting the needs of all small stations, the remaining small vehicles and all large vehicles are used to meet the needs of ordinary stations, that is:

[0088]

[0089] Where: C l is the total capacity of the second vehicle, is the remaining capacity of all first vehicles, m is the number of second stations, d bj is the material demand of the jth station.

[0090] It should be noted that, when it is judged based on the remaining capacity of all the first vehicles to be delivered and the total capacity of all the second vehicles to be delivered that the material demand of all the second sites cannot be met, that is, when it does not meet the above expression, the number of second vehicles will be increased, and the total capacity of all the second vehicles after the increase in the number of second vehicles will be updated until the remaining capacity of all the first vehicles to be delivered and the total capacity of all the second vehicles after the increase in the number of second vehicles meet the material demand of all the second sites.

[0091] S18. When it is determined that the material demand of all second sites can be met based on the remaining capacity of all first vehicles to be delivered and the total capacity of all second vehicles currently to be delivered, the delivery routes of all first vehicles to be delivered and all second vehicles currently to be delivered are optimized to obtain a target delivery plan.

[0092] In this embodiment, optimizing the delivery paths of all first vehicles to be delivered and all second vehicles currently to be delivered to obtain a target delivery plan includes the following steps:

[0093] 1. Taking the number of all types of vehicles, the routes of all types of vehicles, and the distances between all types of sites as variables, the objective function is constructed with the shortest power material distribution route as the goal;

[0094] 2. Determine the constraints of the objective function, which include vehicle capacity constraints and time window constraints;

[0095] 3. Use the optimization algorithm to solve the optimal solution of the objective function and obtain the target distribution plan.

[0096] The expression of the objective function is as follows:

[0097]

[0098] Where: M is the number of vehicles, x ijk Select the variable for the path, d ij is the distance between site i and site j.

[0099] When optimizing the route, two key constraints need to be considered: vehicle capacity constraint and time window constraint to ensure the effective completion of the delivery task. In order to ensure that the load of each vehicle does not exceed its capacity, the vehicle capacity constraint must be set.

[0100] The expressions of the constraints are as follows:

[0101] For a car v∈V small , the total demand of the small stations required for distribution shall not exceed the capacity of the small vehicle, that is, the vehicle capacity constraint:

[0102]

[0103] For a large vehicle v''∈V large , the total demand of the ordinary stations to be delivered must not exceed the capacity of the large vehicle, that is, the vehicle capacity constraint:

[0104]

[0105] Among them: A i is the i-th first site, C small is the total capacity of the first vehicle, Bj is the jth second site, C large is the total capacity of the second vehicle.

[0106] In some cases, a station will have a specific time window, requiring the vehicle to arrive within the specified time. To meet this requirement, you need to set a time window constraint:

[0107] a i ≤t i ≤ b i ;

[0108] Where: t i is the time when the vehicle arrives at the i-th station, [a i ,b i ] is the time window.

[0109] The above embodiment adopts a "vehicle scheduling and route optimization" architecture. Through the vehicle scheduling module and the route optimization module, it ensures that small vehicles give priority to meeting the needs of small sites, while using the remaining vehicles to efficiently complete the delivery tasks of ordinary sites. Through the dynamic adjustment of the distribution process, the overall logistics efficiency is improved.

[0110] Embodiment 2

[0111] See also Figure 2 , an embodiment of a multi-vehicle power material optimization distribution system of the present invention comprises the following steps:

[0112] A site list acquisition unit, used to acquire a site list for power material distribution and material demand quantities corresponding to different types of sites, the site list including a first site and a second site;

[0113] A site information and capacity information traversal unit, used to traverse all site information and capacity information of all vehicle types in the site list, where all vehicle types include the first vehicle and the second vehicle;

[0114] A material demand determination unit for satisfying all first stations, used to determine whether the total capacity of all first vehicles to be delivered can satisfy the material demand of all first stations;

[0115] The remaining capacity calculation unit of the first vehicle is used to calculate the remaining capacity of all the first vehicles to be delivered after the material demands of all the first stations are met, when the total capacity of all the first vehicles to be delivered can meet the material demands of all the first stations;

[0116] A unit for determining the material demand of all second sites, used for determining whether the material demand of all second sites is met based on the remaining capacity of all first vehicles to be delivered and the total capacity of all second vehicles to be delivered;

[0117] The target delivery plan determination unit is used to optimize the delivery routes of all the first vehicles to be delivered and all the second vehicles currently to be delivered to obtain a target delivery plan when it is judged that the material demand of all the second sites can be met based on the remaining capacity of all the first vehicles to be delivered and the total capacity of all the second vehicles currently to be delivered.

[0118] For the specific definition of the system, please refer to the definition of the method above, which will not be repeated here. Each module in the above system can be implemented in whole or in part by software, hardware and a combination thereof. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0119] Embodiment 3

[0120] See also Figure 3 The present invention provides a computer device, including a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor. When the processor executes the computer-readable instructions, the steps of the above method are implemented.

[0121] Those of ordinary skill in the art will appreciate that the units of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition of each example has been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0122] In the embodiments provided by the present invention, it should be understood that the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units can be combined into one unit, one unit can be split into multiple units, or some features can be ignored. In addition, each functional unit in each embodiment of the present invention can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units.

[0123] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-0nlyMemory), random access memory (RAM, RandomAccessMemory), mobile hard disk, magnetic disk or optical disk, etc., which can store program code.

[0124] It can be understood that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A multi-type power material optimization distribution method, characterized in that: include: Obtaining a list of power material distribution sites and material demand quantities corresponding to different types of sites, wherein the list of sites includes first-type sites and second-type sites; Traversing all site information and capacity information of all vehicle types in the site list, wherein all vehicle types include a first vehicle and a second vehicle; Determine whether the total capacity of all first vehicles to be delivered can meet the material demand of all first stations; If so, after satisfying the material requirements of all first stations, the remaining capacity of all first vehicles to be delivered is calculated; Determining whether the material demand of all the second sites can be met based on the remaining capacity of all the first vehicles to be delivered and the total capacity of all the second vehicles to be delivered; If so, the delivery paths of all the first vehicles to be delivered and all the second vehicles currently to be delivered are optimized to obtain a target delivery plan.

2. The multi-type power material optimization distribution method according to claim 1 is characterized in that: The determining whether the total capacity of all first vehicles to be delivered can meet the material demand of all first sites includes: If not, the number of first vehicles is increased, and the total energy of all first vehicles after the increase in the number of the first vehicles is updated until the total capacity of all first vehicles can meet the material demand of all first sites.

3. The multi-type power material optimization distribution method according to claim 2 is characterized in that: The expression until the total capacity of all first vehicles can meet the material demand of all first stations is as follows: Where: C s is the total capacity of all first vehicles, n is the number of first stations, d ai is the material demand of the i-th site.

4. The multi-type power material optimization distribution method according to claim 1 is characterized in that: The determining whether the material demand of all second sites can be met based on the remaining capacity of all first vehicles to be delivered and the total capacity of all second vehicles to be delivered currently includes: If not, increase the number of second vehicles and update the total capacity of all second vehicles after increasing the number of second vehicles until the remaining capacity of all first vehicles to be delivered and the total capacity of all second vehicles after increasing the number of second vehicles meet the material demand of all second sites.

5. The multi-type power material optimization distribution method according to claim 1 is characterized in that: The expression for the remaining capacity of all first vehicles to be delivered and the total capacity of all second vehicles after adding the number of the second vehicles to meet the material demand of all second sites is as follows: Where: C l is the total capacity of the second vehicle, is the remaining capacity of all first vehicles, m is the number of second stations, d bj is the material demand of the jth site.

6. The multi-type power material optimization distribution method according to any one of claims 1-5, characterized in that: The optimizing the delivery paths of all the first vehicles to be delivered and all the second vehicles currently to be delivered to obtain a target delivery plan includes: The objective function is constructed with the number of all types of vehicles, the routes of all types of vehicles, and the distances between all types of sites as variables and the shortest distribution route of power supplies as the goal; Determining constraints of the objective function, wherein the constraints include vehicle capacity constraints and time window constraints; The optimization algorithm is used to solve the optimal solution of the objective function to obtain the target distribution plan.

7. The multi-type power material optimization distribution method according to claim 6 is characterized in that: The expression of the objective function is as follows: Where: M is the number of vehicles, V is the number of stations, x ijk Select the variable for the path, d ij is the distance between site i and site j; The expressions of the constraints are as follows: Vehicle capacity constraints: Among them: A i is the i-th first site, C small is the total capacity of the first vehicle, B j is the jth second site, C large is the total capacity of the second vehicle; Time window constraints: a i ≤t i ≤b i ; Where: t i is the time when the vehicle arrives at the i-th station, [a i ,b i ] is the time window.

8. A multi-model power material optimization distribution system, characterized in that: include: A site list acquisition unit, used to acquire a site list for power material distribution and material demand quantities corresponding to different types of sites, wherein the site list includes a first site and a second site; A site information and capacity information traversal unit, used to traverse all site information and capacity information of all vehicle types in the site list, wherein all vehicle types include a first vehicle and a second vehicle; A material demand determination unit for satisfying all first stations, used to determine whether the total capacity of all first vehicles to be delivered can satisfy the material demand of all first stations; The remaining capacity calculation unit of the first vehicle is used to calculate the remaining capacity of all the first vehicles to be delivered after the material demands of all the first stations are met, when the total capacity of all the first vehicles to be delivered can meet the material demands of all the first stations; A material demand determination unit for satisfying all second sites, configured to determine whether the material demand of all second sites is satisfied based on the remaining capacity of all first vehicles to be delivered and the total capacity of all second vehicles to be delivered; The target delivery plan determination unit is used to optimize the delivery routes of all the first vehicles to be delivered and all the second vehicles to be delivered when it is judged that the material demand of all the second sites can be met based on the remaining capacity of all the first vehicles to be delivered and the total capacity of all the second vehicles to be delivered, so as to obtain the target delivery plan.

9. A computer device, characterized in that: include: memories, transceivers, processors, and bus systems; Wherein, the memory is used to store programs; The processor is used to execute the program in the memory, including executing the multi-vehicle power material optimization distribution method according to any one of claims 1 to 7; The bus system is used to connect the memory and the processor so that the memory and the processor can communicate with each other.

10. A readable storage medium, characterized in that: It includes instructions, which, when executed on a computer, enable the computer to execute the multi-vehicle electric material optimization distribution method as described in any one of claims 1 to 7.

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