The swap mode,with its efficient and convenient form battery exchange,will become the mainstream way of supplement energy for the future,and whether the site selection of the battery swap station is reasonable has a significant impact on investment decisions and transportation travel.This paper based on minimizing construction cost of battery swap stations and the cost of user travel,as well as maximizing user coverage as the objective function,designs an improved non-dominated sorting genetic algorithm(NSGA-II)with elite strategy to solve the dual objective mixed integer programming model and obtain the pareto optimal solution set.Taking numerical simulation as an example,verifies the feasibility of model construction,providing a methodological basis for the planning of the electric vehicle battery swap station network.
关键词
电动汽车/换电站/选址问题/遗传算法
Key words
Electric Vehicle/Battery Swap Station/Facility Location Problem/Genetic Algorithm
维普
万方数据