Study On Electric Vrp With Soft Time Windows And Charging Stations

Recently,serious air pollution exists in most big cities of China,fuel vehicle emissions is the major cause of the situation,on the other hand,fossil energy gradually decreases.Above all,the efficiency use of clean energy is way to solve the current situation.Pure electric vehicles have high energy efficiency,low noise and zero emissions,so the use of pure electric vehicles for logistics distribution has gained national policy support,and already have the basis of the popularization and application.But pure electric vehicles are different from fuel cars.They have short driving range and long charging time,and they need to consider the situation of entering the charging station to fill up energy in the course of the distribution.Firstly,this paper combined with the traditional vehicle routing optimization experience and the characteristics of the electric car in order to set up EVRPSTW(Electric Vehicle Routing Problem with Recharging Station and Time Windows,EVRPSTW) model,then extend it from a single distribution center problem to a multiple distribution centers problem(MDEVRPSTW,Multiple Depot Electric Vehicle Routing Problem with Recharging crisis and Time Windows).The model considers the Vehicle cost,transportation cost,energy cost and Time Windows’ penalty cost.Secondly,according to the comparison of the basic particle swarm algorithm and particle swarm algorithm with adaptive weighted,we can prove that the improved particle swarm algorithm has overcome the defect that traditional particle swarm algorithm is easy to fall into a local optimal solution.In the solution of MDEVRPSTW,the "holistic method" and "cropping method" are put forward to prove that the "cropping method" is superior to "holistic method" in the searching time and searching ability.Thirdly,based on the classic VRPTW Solomon data,this paper applicate MATLAB software for programming realize and example analysis four times and all kinds of cost and algorithm parameters that affect the vehicle path planning are analyzed,this paper also compared the advantages and disadvantages of many kinds of algorithm,and gives best distribution scheme of single distribution center and multiple distribution center optimal problems The result is extensibility,if data is changed we can till obtain the best distribution plan easily.This study has theoretical reference value for the development of traditional vehicle route planning problems and the application of improved particle swarm algorithm,and also has practical significance for promoting the promotion of electric vehicle logistics.