Research On Joint Modeling And Optimization Of Shared Electric Vehicle Rental Station Location And Scheduling

In recent years,the combination of shared electric vehicles and the Internet has led to a new trend of diversified transportation development.Through the correct layout of the shared electric vehicle rental network and the reasonable scheduling of vehicles,the travel needs of travelers can be met,the service quality can be improved,the shared electric vehicles have been developed accordingly,and the number of private cars can be effectively reduced,which is in line with the state advocated.Energy saving and green development concept.This paper first analyzes the research background of shared electric vehicle network location and vehicle scheduling,and clarifies the research significance of the topic.Then,it summarizes and summarizes the research on site selection,operation mode,vehicle scheduling,and the joint site selection and vehicle scheduling at home and abroad,analyzes the lessons of the existing research,finds the problems existing in the existing research,and clarifies this paper.The main content of the study.Secondly,an overview of shared electric vehicles is introduced,in which the operation modes of shared electric vehicles,including Car2 go leasing mode and P2 P leasing mode,are analyzed,and the operating characteristics of the two are analyzed;the advantages of shared electric vehicles such as energy saving and environmental protection are listed.,and the problems it faces in its development;an overview of network site location planning and vehicle scheduling.Thirdly,considering the factors of distance between outlets,customer demand factors and vehicle charging factors,this paper establishes a mathematical model with the goal of minimizing the total distance between outlets and demand points and maximizing the operating profit of shared electric vehicle companies.Then,by summarizing and analyzing the research methods of location selection and scheduling problems at home and abroad,it is concluded that genetic algorithm is a common method to solve such problems.However,in this paper,the immune optimization algorithm is selected to solve the model.Compared with the traditional genetic algorithm,the immune algorithm solves the problem of the genetic algorithm being prone to premature maturity.This paper focuses on the basic principles and algorithm flow of the immune algorithm,including antibody design,fitness calculation,antibody selection,and population update steps,and expounds the working ideas and specific processes of the solution.Finally,collect and organize the network data of Anning District,Chengguan District and Qilihe District of Lanzhou City,determine the parameters needed in the model solution,and compare and analyze the results obtained by the genetic algorithm and the immune optimization algorithm respectively.The results show that the latter is better than the former.,to obtain a site selection layout plan with a shorter total distance between outlets and demand points,and a more profitable vehicle scheduling scheme for enterprise operations,which verifies the operability and effectiveness of the immune algorithm for site selection and research problems.Considering the influence of the number of outlets and the number of vehicles on the results,a sensitivity analysis of the two influencing factors was carried out.The results show that the construction of an appropriate number of outlets in the site selection model can significantly reduce the cost of early outlet construction,and the outlet coverage rate remains at relatively high level.In the scheduling model,the analysis finds that investing in the appropriate number of vehicles can reduce vehicle acquisition costs,and the vehicle utilization rate is high,and most customer needs will be met.