Research On Electric Vehicle Routing Problem Considering Time-dependent Speed

In recent years,the rapid development of logistics transportation industry and the increasingly complex urban distribution network make urban traffic congestion more and more serious.Most of the literature on traditional vehicle routing problem assumes that the vehicle speed is constant.In fact,due to the frequent traffic congestion and speed limit on urban roads,the driving speed of vehicles will be time-varying,that is,the driving speed of vehicles at different times is different.In addition,the logistics transportation industry has also led to increasingly serious environmental pollution,which makes the logistics industry become one of the industries with serious pollution and energy consumption.Electric vehicles can achieve zero greenhouse gas emissions and low energy consumption during driving while meeting the needs of urban logistics and distribution,therefore,it has become a trend for the future development of the automobile industry and logistics industry that electric vehicles replace fuel vehicles.However,the range of electric vehicles generally cannot meet long-distance transportation tasks,and it takes a long time for electric vehicles to be fully charged,therefore,when planning the routing of electric vehicles,the VRP model of traditional fuel vehicles can no longer be completely copied.So,in the use of electric vehicles for logistics transportation,how to optimize the vehicle distribution path and improve the efficiency of logistics transportation is particularly important.In this context,considering the common factors of electric vehicles and time-varying speed in urban logistics distribution,based on the static customer demand problem,the vehicle routing problem of multi-objective electric vehicle routing problem with time-varying speed is studied.Then an integer programming model of the problem is established,which aims to minimize the deviation of the time window and the total operating cost.Then to solve this problem,a hybrid heuristic algorithm based on multi-objective particle swarm optimization and variable neighborhood search algorithm is proposed,this algorithm uses the variable neighborhood search algorithm to search the particle path,which can search the solution space efficiently.Finally,the pareto solution set of the multi-objective hybrid particle swarm optimization algorithm under different customer distribution conditions is given,which verifies the effectiveness of the model and the algorithm.On the basis of considering the time-varying speed electric vehicle routing problem under static demand,aiming at the dynamic characteristics of customer demand in modern logistics distribution systems,the problem of electric vehicle routing problem considering time-dependent speed and dynamic demand is studied.Firstly,the "wait-and-see" strategy is adopted to model the dynamic demands and the mixed integer programming model of its static sub-problem is established.Then a solution algorithm based on time-domain partitioning is proposed: the dynamic customers are cyclically processed during the vehicle service process,and the simulated annealing algorithm combined with variable neighborhood search is proposed to solve the current customer set with known information in the time domain.Finally,12 test cases of different types and scales are constructed from Solomon standard cases,the results of static example test and the results of dynamic rate analysis prove the validity of the EVRP-TSDD mathematical model and the algorithm in this paper,the time domain length analysis results show that a smaller time domain length is more beneficial real-time processing of dynamic customers;the analysis results of dynamic calculation examples further verify the effectiveness of this algorithm in processing dynamic new customers.