Network access method, device and equipment based on multi-target vehicle path planning

Abstract

The embodiment of the invention can be applied to the field of financial science and technology, and discloses a website access method, device and equipment based on multi-target vehicle path planning. The method comprises the following steps: constructing a multi-target vehicle path planning topological graph according to vehicle information owned by a vehicle distribution center and position information of the distribution center, a user and a network point; according to the topological graph, determining a target function and a constraint condition for the vehicle to depart from the distribution center to carry the user to the network point for business handling; wherein the objective functions comprise a cost minimization function, a time minimization function and a service level maximization function; the constraint condition comprises a vehicle capacity constraint; and according to the target function and the constraint condition, carrying out optimal solution solving, and determining a target network point accessed by the user under the multi-target vehicle path planning. The optimal distribution path can be screened out by considering the optimization problem of network access of the user under multi-target vehicle path planning, so that the time and the cost are saved, and the user service quality is improved.

Description

Technical Field

[0001] The present invention relates to the field of financial technology, and in particular to a network access method, device and equipment based on multi-objective vehicle path planning. Background Art

[0002] With the development of financial technology, online business processing technology in the field of financial technology has been continuously improved, and users rarely choose offline outlets to conduct business. Therefore, when it is not necessary to go to offline outlets to conduct business, it is necessary to achieve the purpose of speed and efficiency.

[0003] In order to reach the nearest outlet quickly, users need to consider not only the road conditions but also the vehicle usage. For example, if a user only chooses to take a taxi alone, it will be difficult to get a taxi during peak hours. At this time, even if the nearest outlet is chosen, the journey may be long, causing the user to miss the earliest time to handle offline business, resulting in the opposite result. For another example, if a user chooses the nearest outlet, but there are too many users handling business at the current outlet, users will have to wait for a long time, which is contrary to the original intention of fast and efficient business handling.

[0004] Based on the above considerations, the inventor proposed a network point access method based on multi-objective vehicle path planning in actual research and development to optimize the process of users visiting network points to handle business, saving time and cost. Summary of the invention

[0005] The present invention provides a network point access method, device and equipment based on multi-objective vehicle path planning, so as to optimize the process of users visiting network points to handle business, thereby saving time and cost.

[0006] According to one aspect of the present invention, a network point access method based on multi-objective vehicle path planning is provided, the method comprising:

[0007] Based on the vehicle information owned by the vehicle distribution center, as well as the location information of the distribution center, users and outlets, a multi-objective vehicle path planning topology map is constructed;

[0008] According to the topology diagram, determine the objective function and constraints of the vehicle transporting users from the distribution center to the outlets for business processing;

[0009] Wherein, the objective function includes minimizing the cost function, minimizing the time function and maximizing the service level function; the constraint condition includes the vehicle capacity constraint;

[0010] According to the objective function and the constraints, an optimal solution is obtained to determine the target network points visited by the user under the multi-objective vehicle path planning.

[0011] According to another aspect of the present invention, a network point access device based on multi-objective vehicle path planning is provided, the device comprising:

[0012] The topology map construction module is used to construct a multi-objective vehicle path planning topology map based on the vehicle information owned by the vehicle distribution center and the location information of the distribution center, users and outlets;

[0013] A network point access model building module is used to determine the objective function and constraints of vehicles transporting users from the distribution center to the network point for business processing based on the topological map;

[0014] Wherein, the objective function includes minimizing the cost function, minimizing the time function and maximizing the service level function; the constraint condition includes the vehicle capacity constraint;

[0015] The target network point determination module is used to solve the optimal solution according to the objective function and the constraint conditions, and determine the target network points visited by the user under the multi-objective vehicle path planning.

[0016] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0017] at least one processor; and

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the network point access method based on multi-objective vehicle path planning described in any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the network point access method based on multi-objective vehicle path planning described in any embodiment of the present invention when executed.

[0021] According to another aspect of the present invention, a computer program product is provided, including a computer program, which, when executed by a processor, implements the network point access method based on multi-objective vehicle path planning described in any embodiment of the present invention.

[0022] The technical solution of the embodiment of the present invention is to construct a multi-objective vehicle path planning topology map based on the vehicle information owned by the vehicle distribution center and the location information of the distribution center, users and outlets; based on the topology map, determine the objective function and constraints of the vehicle carrying users from the distribution center to the outlets for business processing; wherein the objective function includes minimizing the cost function, minimizing the time function and maximizing the service level function; the constraints include vehicle capacity constraints; based on the objective function and the constraints, the optimal solution is solved to determine the target outlets visited by users under the multi-objective vehicle path planning, thereby solving the path optimization problem of users visiting the outlets and saving the time and cost of users going to the outlets for business processing.

[0023] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 is a flow chart of a network point access method based on multi-objective vehicle path planning provided according to an embodiment of the present invention;

[0026] Figure 2 is a flow chart of another network point access method based on multi-objective vehicle path planning provided according to an embodiment of the present invention;

[0027] Figure 3 It is a structural schematic diagram of a network point access device based on multi-objective vehicle path planning provided according to an embodiment of the present invention;

[0028] Figure 4 It is a structural schematic diagram of an electronic device for implementing a network point access method based on multi-objective vehicle path planning according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention 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 interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof 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.

[0031] Figure 1 It is a flowchart of a network point access method based on multi-objective vehicle path planning provided according to an embodiment of the present invention. This embodiment can be applicable to the path optimization situation when a user visits a network point to handle business through a vehicle. The method can be executed by a network point access device based on multi-objective vehicle path planning. The network point access device based on multi-objective vehicle path planning can be implemented in the form of hardware and / or software. The network point access device based on multi-objective vehicle path planning can be configured in an electronic device such as a computer.

[0032] In an embodiment of the present invention, the path optimization problem of users accessing outlets by vehicle can be considered as a vehicle routing problem based on heterogeneous capacity (HCVRP). HCVRP is one of the variant problems of the vehicle routing problem. Starting from the characteristics of different vehicle loads, the heterogeneity of vehicle capacity is mainly studied. The optimization problem of the embodiment of the present invention can be described as: the vehicle distribution center is composed of a number of vehicles to provide services to various user points. The vehicle starts from the distribution center, serves each user and outlet in turn, and finally returns to the vehicle distribution center. During the distribution process, the vehicle capacity is uncertain, and each user and outlet can be reached and is only served once.

[0033] Based on the above description, vehicle trajectory dataset, and network point distribution, we can construct a network point access optimization problem based on multi-objective vehicle path planning. Figure 1 As shown, the network point access method based on multi-objective vehicle path planning provided by the embodiment of the present invention includes:

[0034] Step 110: construct a multi-objective vehicle path planning topology map based on the vehicle information owned by the vehicle distribution center and the location information of the distribution center, users and outlets.

[0035] Among them, the distribution center's vehicle information, location information, outlet waiting time and other information are obtained only after user authorization, and the method of obtaining is reasonable and legal.

[0036] Specifically, N = {0, 1, ..., i, ..., n} represents the vehicle distribution center, each user and outlet, where i∈N, 0≤i≤n, and i = 0 represents the distribution center, and i = 1, ..., n represents n customer points (users and outlets). (x i ,y i ) represents the location of the distribution center and the customer point. In the distribution center, M = {1, ..., j, ..., m} vehicles of different types and loads are used to transport users. R j represents the maximum load of vehicle j. When a vehicle transports any user, the number of users carried along cannot exceed the maximum load of the vehicle. i ,L i ] represents the expected waiting time range of the user at the network point i. w represents the acceptable waiting time of the user. The initial user scale can be set to 20, 50, and 100, etc., and the multi-objective vehicle path planning topology map is constructed by combining the location coordinates of users and network points, the maximum load of the vehicle, the number of people waiting at the network point, and other factors.

[0037] Step 120: According to the topology diagram, determine the objective function and constraints for the vehicle to transport the user from the distribution center to the outlet for business processing.

[0038] In the topology diagram where vehicles depart from the distribution center to transport users to outlets for business processing, it is required to simultaneously achieve multiple goals such as the lowest distribution cost among all vehicles, the shortest total distribution time, the shortest distribution time for a single route, and the shortest distribution path. Based on this requirement, the objective function and constraints can be constructed. Specifically, the objective function includes minimizing the cost function, minimizing the time function, and maximizing the service level function; the constraints include vehicle capacity constraints.

[0039] The minimization cost function may take into account various situations. For example, the minimization cost function may include at least one of the following cost factors: the startup cost of the distribution center vehicle carrying the user, the transportation cost of the vehicle carrying the user to the outlet, and the waiting penalty cost incurred by the user waiting at the outlet.

[0040] Optionally, the cost function can be determined in the following way: based on the startup cost of the distribution center vehicle carrying the user, the transportation cost of the vehicle carrying the user to the outlet, and the waiting penalty cost incurred by the user waiting at the outlet, the cost function of transporting the user to the outlet by the distribution center vehicle is determined.

[0041] Specifically, in the embodiment of the present invention, the minimization cost function can be expressed as In the formula, C represents the vehicle startup cost, F represents the transportation cost, and T represents the penalty cost for users waiting too long at the outlet. iom X is a binary decision variable, indicating that vehicle m sends user i to network point o. im is a binary decision variable, indicating that vehicle m carries user i. Therefore, the expression for minimizing the cost function can be specifically understood as follows: the first term is the startup cost of vehicle m carrying user i. The second term is the transportation cost of vehicle m sending user i to outlet o. The third term is the penalty cost for users waiting too long at outlet i. Each cost value can be set according to actual conditions, and the embodiment of the present invention does not make specific limitations on this. By considering the minimization of the cost function in the path planning when the user visits the outlet, the vehicle cost and the user time cost when the user visits the outlet can be reduced, thereby ensuring the low cost requirement for the user to visit the outlet.

[0042] The minimization time function may be to minimize the time it takes for the user to reach the outlet. In the embodiment of the present invention, optionally, the time function may be determined in the following manner: according to the distance from the user to the outlet, the vehicle speed, and the allocation of the vehicle for transporting the user to the outlet in the topology map, the time function for transporting the user to the outlet by the distribution center vehicle is determined.

[0043] Specifically, in the embodiment of the present invention, the expression for minimizing the time function may be: In the formula, D(x i ,y o ) represents the distance from user i to network point o, f represents the unit speed, Y im is a binary decision variable, indicating that user i is only served by vehicle m. Therefore, the minimized time function is the time required for vehicle m to transport user i to outlet o. By considering the minimized time function in the path planning when users visit outlets, the efficiency of users visiting outlets can be improved, ensuring that users arrive at outlets in time for business processing.

[0044] The maximized service level function may be to maximize the degree of agreement between the time a user spends on business processing at a branch and the reference waiting time provided by the branch. In an embodiment of the present invention, the service level function may optionally be determined in the following manner: according to the actual path time consumed when a user visits a branch in the topology diagram, the estimated waiting time range provided by the branch, and the acceptable waiting time for the user, the service level function of the user at the branch is determined.

[0045] For example, when determining the service level function, the higher the service level is when the actual path time taken by the user to access the network point falls within the estimated waiting time range provided by the network point; and the farther it deviates from the estimated waiting time range, the lower the service level is. Specifically, the expression for maximizing the service level function can be: In the formula, e im represents the actual path time when vehicle m carries user i, w represents the user's acceptable waiting time, [E i ,L i ] represents the estimated waiting time range of users at branch i provided by the branch, E i is the lower limit of waiting time, L i is the upper limit of waiting time, S i It indicates the customer's experience of handling offline business this time, that is, the service level. In the function of maximizing the service level, the closer the service level is to 1, the better the service level is; the closer it is to 0, the worse the service level is. In the embodiment of the present invention, it is believed that the closer the time from the user's taxi to the outlet is to the estimated waiting time range provided by the outlet, the higher the service level is; the further it deviates from the estimated waiting time range, the lower the service level is.

[0046] By considering the maximization of the service level function in the path planning when users visit the outlets, the service level of users visiting the outlets for business processing can be improved, ensuring that users can conduct efficient business processing at the outlets.

[0047] In the embodiment of the present invention, a multi-objective function in the network point access based on multi-objective vehicle path planning can be formed according to the minimization of cost function, minimization of time function and maximization of service level function. After constructing the multi-objective function, constraints can also be constructed. Among them, the constraints include vehicle capacity constraints, that is, the number of users carried along cannot exceed the maximum load capacity R of the vehicle in the process of transporting any user by the vehicle. j .

[0048] On the basis of the above implementation mode, optionally, the constraint conditions can be further determined in the following manner: based on the soft time window constraints for users to take taxis and conduct business at outlets in the topology diagram, as well as the vehicle capacity constraints, the constraint conditions for vehicles to transport users from distribution centers to outlets for business processing are determined.

[0049] Among them, the soft time window constraint for users to take a taxi and handle business at the outlets can be understood as a flexible constraint on the time for users to take a taxi and handle business at the outlets, limiting the time within a certain time range, but allowing a certain degree of deviation outside this time range. When the time deviates from the time range, a certain penalty cost will be incurred, which will not cause the user's access to the outlet to fail. By using the soft time window constraint and vehicle capacity constraint, the actual capacity of heterogeneous vehicles can be guaranteed to be reasonable, and the time spent by users to handle business can be guaranteed to be reasonable.

[0050] Step 130: Find the optimal solution based on the objective function and the constraints to determine the target network point visited by the user under the multi-objective vehicle path planning.

[0051] The optimal solution of multi-objective vehicle path planning problem with heterogeneous capacity can be obtained through traditional mathematical methods and heuristic algorithms. Traditional mathematical methods include but are not limited to: dynamic programming, integer programming, two-stage method, etc. Heuristic algorithms seek the optimal solution through global search, including but not limited to: particle swarm algorithm, genetic algorithm, ant colony algorithm, bat algorithm, and whale algorithm, etc. However, traditional mathematical methods are only effective for small-scale problems. Heuristic algorithms can prevent algorithms from falling into local optimality, but the algorithm process is relatively complicated, and the rationality of parameter settings will greatly affect the algorithm. Moreover, when different algorithms are applied to practical fields, the defects of the algorithms themselves will also bring certain limitations to problem solving.

[0052] In the embodiment of the present invention, the inventor conducts a specific analysis of the heuristic algorithm, selects a combination of a genetic algorithm and a multi-objective optimization algorithm, selects the optimal solution, ensures the diversity of solutions through multiple objectives, selects the best delivery route, optimizes the process of users going to outlets to handle business, and saves time and cost.

[0053] Optionally, the optimal solution is solved according to the objective function and constraints, and the target network points visited by the user under the multi-objective vehicle path planning are determined, including: determining the non-dominated solution individuals that satisfy the Pareto dominance relationship in the current optimal solution according to the objective function and constraints, and generating an external partially dominated solution based on all non-dominated solution individuals; performing solution selection, crossover and mutation in the external partially dominated solution to perform iterative optimization; when the iteration termination condition is met, determining the target network points visited by the user under the multi-objective vehicle path planning according to the final external partially dominated solution.

[0054] Among them, the Pareto dominance relationship means that for solutions T1 and T2, if solution T1 is not worse than solution T2 in all objective functions, and is better than solution T2 in at least one objective function, then solution T1 is said to dominate solution T2. ​​This relationship reflects the overall performance advantage of one solution over another in multi-objective optimization. Non-dominated solution individuals, also known as Pareto solutions or undominated solutions, refer to solutions that no other solutions can dominate in multi-objective optimization problems. That is, if a solution is not surpassed by other solutions in all objective functions, then this solution is a non-dominated solution.

[0055] In an embodiment of the present invention, for multi-objective optimization, when f1 and f2 are smaller and f3 is larger, the currently obtained solution is better. For different solutions T1 and T2 that satisfy the constraints, all non-dominated solution individuals in the solution set that satisfy the Pareto dominance relationship of f1(T1)>f1(T2), f2(T1)>f2(T2) and f3(T1)>f3(T2), or f1(T1)<f1(T2), f2(T1)<f2(T2) and f3(T1)<f3(T2) are solved. The external partially dominated solution is generated based on all non-dominated solution individuals.

[0056] In order to extend the solutions of multi-objective optimization operations, improve the diversity of solutions, and better select the optimal solution set for this iteration, solution selection, crossover and mutation can be performed according to genetic algorithms.

[0057] Specifically, the formula as well as Perform solution extension. Among them, P y is the probability of selecting the yth chromosome last time, P y ' is the probability of selecting the yth chromosome in the previous selection, Γ is the number of chromosomes entering the selection process, is the average fitness of all chromosomes entering the selection process; count is the total number of times the current chromosome is repeatedly selected, F max and F min is the maximum and minimum fitness value in the population, F c It is the larger fitness value of the two parents before and after the selection operation. r1~r6 are all random numbers between 0 and 1, and r1>r3, r4>r6. c is the crossover probability, P m is the mutation probability. The fitness value can be determined according to the fitness function. There are many ways to determine the fitness function. For example, the fitness function can be determined according to a multi-objective function. Alternatively, the individuals in the population can be sorted according to the Pareto dominance relationship, and a fitness value can be assigned to each individual according to the sorting result. The higher the individual is in the ranking, the higher the fitness value is, and thus the more likely it is to be selected to the next generation.

[0058] When selecting the optimal solution, iterative optimization can be performed, and whether to continue iteration can be determined by the iteration termination condition. Among them, the iteration termination condition can be that the current iteration number reaches the maximum iteration number. At this time, the external partial dominated solution is the optimal solution set under the multi-objective vehicle path planning. According to the path corresponding to the optimal solution, the result of the vehicle carrying users to visit the network point is determined to ensure the diversity of the solution, meet the minimum cost, minimum time and maximum service level, and ensure the vehicle capacity.

[0059] The technical solution of this embodiment is to construct a multi-objective vehicle path planning topology map based on the vehicle information owned by the vehicle distribution center and the location information of the distribution center, users and outlets; based on the topology map, determine the objective function and constraints of the vehicle transporting users from the distribution center to the outlets for business processing; wherein the objective function includes minimizing the cost function, minimizing the time function and maximizing the service level function; the constraints include vehicle capacity constraints; based on the objective function and the constraints, the optimal solution is solved to determine the target outlets visited by users under the multi-objective vehicle path planning, thereby solving the path optimization problem of users visiting outlets and saving the time and cost of users going to the outlets for business processing.

[0060] Figure 2 FIG. 1 is a flowchart of another network point access method based on multi-objective vehicle path planning according to an embodiment of the present invention. Figure 2 As shown, a specific application example of the network access method based on multi-objective vehicle path planning provided by an embodiment of the present invention is: based on the trajectory data sets of the transport center, the vehicle, and the user, and the network distribution set, a multi-objective vehicle path planning topology map (road network topology map) is constructed. A multi-objective function of minimizing cost, minimizing time, and maximizing service level is set to solve all non-dominated solutions of the initial population. When screening the optimal solution, constraints can be added: vehicle capacity constraints, and soft time window constraints for users to take a taxi and wait at the network point. When the iteration termination condition is not met, the current optimal solution is repeatedly screened according to the selection operator, the optimal solution is globally updated according to the adaptive crossover and mutation operators, and the non-dominated solution is updated according to the multi-objective optimization operation. When the iteration terminates, the optimal solution set is output.

[0061] By adopting a hybrid genetic algorithm, the traditional genetic algorithm is transformed, the initial solution is screened out by orthogonal experiments, and the global search capability is improved by adaptive crossover operators and mutation operators. The diversity of solutions can be guaranteed by multi-objective functions. In the multi-objective process of achieving minimum cost, shortest delivery route and maximum service level, the capacity of vehicles, the number of people waiting at outlets, and the soft time window waiting of customers are used as constraints to select the optimal solution obtained at each step, so that users can efficiently handle offline business while improving the quality of handling business, avoiding waiting longer due to the uncertainty of the number of people waiting at offline outlets. Therefore, based on the multi-objective optimization operation, multiple routes that can reach the outlets as quickly as possible can be screened for users, reducing the total time of the user's business handling process and improving the user's offline business handling experience. It effectively breaks the limitations of users' taxi selection and the non-real-time update of outlet information. In the entire method process, a new idea is provided for users to plan the path for handling business at offline outlets. In addition, from the perspective of vehicle capacity, soft time window constraints are added to the waiting time of users at outlets, which increases the probability of users taking a car and reduces the time for users to take a taxi and wait for a car. The embodiments of the present invention can also display the waiting time required for offline business processing at various outlets on major platforms, so as to facilitate users to better screen the best outlets for offline business processing, effectively reduce the time for users to process business at outlets, and provide a higher quality solution for users' path planning for offline business processing.

[0062] Figure 3 is a schematic diagram of the structure of a network point access device based on multi-objective vehicle path planning according to an embodiment of the present invention. Figure 3 As shown, the device includes: a topology map building module 310, a network point access model building module 320, and a target network point determination module 330. Among them:

[0063] A topology map construction module 310 is used to construct a multi-objective vehicle path planning topology map based on the vehicle information owned by the vehicle distribution center and the location information of the distribution center, users and outlets;

[0064] The network point access model building module 320 is used to determine the objective function and constraint conditions of the vehicle transporting users from the distribution center to the network point for business processing according to the topology map;

[0065] Among them, the objective function includes minimizing the cost function, minimizing the time function and maximizing the service level function; the constraints include the vehicle capacity constraint;

[0066] The target network point determination module 330 is used to solve the optimal solution according to the objective function and the constraint conditions, and determine the target network points visited by the user under the multi-objective vehicle path planning.

[0067] Optionally, the website access model building module 320 includes:

[0068] The cost function determination unit is used to determine the cost function of transporting users to the outlets by the distribution center vehicles according to the startup cost of the distribution center vehicles transporting users, the transportation cost of the vehicles transporting users to the outlets, and the waiting penalty cost incurred by the users waiting at the outlets in the topology diagram.

[0069] Optionally, the website access model building module 320 includes:

[0070] The time function determination unit is used to determine the time function for transporting users to the network point by the distribution center vehicle according to the distance from the user to the network point, the vehicle speed, and the allocation of vehicles for transporting users to the network point in the topology map.

[0071] Optionally, the website access model building module 320 includes:

[0072] The service level function determination unit is used to determine the service level function of the user at the network point according to the actual path time consumed by the user when accessing the network point in the topology map, the estimated waiting time range provided by the network point, and the user's acceptable waiting time.

[0073] Optionally, the website access model building module 320 includes:

[0074] The constraint determination unit is used to determine the constraint conditions for vehicles to transport users from distribution centers to outlets for business processing based on the soft time window constraints for users to take taxis and conduct business at outlets in the topology map, as well as the vehicle capacity constraints.

[0075] Optionally, the target network point determination module 330 includes:

[0076] An external partially dominated solution generating unit is used to determine the non-dominated solution individuals that satisfy the Pareto dominance relationship in the current optimal solution according to the objective function and the constraint conditions, and generate an external partially dominated solution according to all the non-dominated solution individuals;

[0077] Iterative optimization unit, used for solution selection, crossover and mutation in the external partially dominated solution, and iterative optimization;

[0078] The target network point determination unit is used to determine the target network point visited by the user under the multi-objective vehicle path planning according to the final external partial control solution when the iteration termination condition is met.

[0079] The network point access device based on multi-objective vehicle path planning provided in the embodiment of the present invention can execute the network point access method based on multi-objective vehicle path planning provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0080] In the technical solution of the embodiment of the present invention, the information involved (such as vehicle information, user location information, and branch location information, etc.) is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with the relevant laws, regulations and standards of the relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0081] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0082] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0083] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0084] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a network point access method based on multi-objective vehicle path planning.

[0085] In some embodiments, the network point access method based on multi-target vehicle path planning can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the network point access method based on multi-target vehicle path planning described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the network point access method based on multi-target vehicle path planning by any other appropriate means (for example, by means of firmware).

[0086] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0087] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0088] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0089] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0090] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0091] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0092] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0093] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A network point access method based on multi-objective vehicle path planning, characterized in that: include: Based on the vehicle information owned by the vehicle distribution center, as well as the location information of the distribution center, users and outlets, a multi-objective vehicle path planning topology map is constructed; According to the topology diagram, determine the objective function and constraints of the vehicle transporting users from the distribution center to the outlets for business processing; Wherein, the objective function includes minimizing the cost function, minimizing the time function and maximizing the service level function; the constraint condition includes the vehicle capacity constraint; According to the objective function and the constraints, an optimal solution is obtained to determine the target network points visited by the user under the multi-objective vehicle path planning.

2. The method according to claim 1, characterized in that According to the topology diagram, determine the objective function and constraints of the vehicle transporting users from the distribution center to the outlet for business processing, including: According to the topology diagram, the startup cost of the distribution center vehicle carrying the user, the transportation cost of the vehicle carrying the user to the outlet, and the waiting penalty cost incurred by the user waiting at the outlet, the cost function of transporting the user to the outlet by the distribution center vehicle is determined.

3. The method according to claim 1, characterized in that According to the topology diagram, determine the objective function and constraints of the vehicle transporting users from the distribution center to the outlet for business processing, including: According to the distance from the user to the network point, the vehicle speed, and the allocation of vehicles for transporting the user to the network point in the topology diagram, the time function for transporting the user to the network point by the distribution center vehicle is determined.

4. The method according to claim 1, characterized in that According to the topology diagram, determine the objective function and constraints of the vehicle transporting users from the distribution center to the outlet for business processing, including: The service level function of the user at the network point is determined based on the actual path time consumed when the user visits the network point, the estimated waiting time range provided by the network point, and the user's acceptable waiting time in the topology map.

5. The method according to claim 1, characterized in that According to the topology diagram, determine the objective function and constraints of the vehicle transporting users from the distribution center to the outlet for business processing, including: Based on the soft time window constraints for users to take taxis and conduct business at outlets, as well as the vehicle capacity constraints in the topology diagram, the constraints for vehicles to transport users from the distribution center to the outlets for business processing are determined.

6. The method according to claim 1, characterized in that According to the objective function and the constraints, an optimal solution is obtained to determine the target network points visited by the user under the multi-objective vehicle path planning, including: According to the objective function and the constraint conditions, determine the non-dominated solution individuals that satisfy the Pareto dominance relationship in the current optimal solution, and generate the external partially dominated solution according to all the non-dominated solution individuals; Selecting solutions, performing crossover and mutation in the external partial dominated solutions, and performing iterative optimization; When the iteration termination condition is met, the target network point visited by the user under the multi-objective vehicle path planning is determined according to the final external partial dominated solution.

7. A network point access device based on multi-objective vehicle path planning, characterized in that: include: The topology map construction module is used to construct a multi-objective vehicle path planning topology map based on the vehicle information owned by the vehicle distribution center and the location information of the distribution center, users and outlets; A network point access model building module is used to determine the objective function and constraints of vehicles transporting users from the distribution center to the network point for business processing based on the topological map; Wherein, the objective function includes minimizing the cost function, minimizing the time function and maximizing the service level function; the constraint condition includes the vehicle capacity constraint; The target network point determination module is used to solve the optimal solution according to the objective function and the constraint conditions, and determine the target network points visited by the user under the multi-objective vehicle path planning.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the network point access method based on multi-objective vehicle path planning as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the network point access method based on multi-objective vehicle path planning according to any one of claims 1 to 6 when executed.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the network point access method based on multi-objective vehicle path planning according to any one of claims 1 to 6 is implemented.

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