摘要
为解决移动充电平台投入运营成本高的问题,考虑应急服务点时间窗、流量平衡及充电车里程限制等约束,建立包括移动充电车为应急服务点提供充电服务的车辆启动成本、行驶成本和违反应急服务点的时间窗惩罚成本三者总和最小的混合整数非线性规划模型,通过分支定界法和遗传算法研究了半开放式的多车场移动充电车路径优化问题。结果表明:对半开放式的多车场移动充电车路径优化问题进行10次求解,每次运行得到的解与10次中最优解的偏差(g ap)均值为1.22%,说明遗传算法具有良好的稳定性;与单车场独立服务模式对比分析,半开放式多车场联合服务可为移动充电车提供更多路径选择,减少充电车行驶里程,降低平台运营成本;对比顾客点集中分布情形,在顾客点随机分布和混合分布情形下,移动充电平台的成本节约效果更为显著。
To solve the problem of high operation cost of mobile charging platform,the mixed integer non-linear programming model with the minimum sum of vehicle start-up cost,driving cost and penalty cost of violating the time window of emergency service points was established,considering the constraints of emergency service points time window,flow balance and charging vehicles mileage limitation,the mobile charging vehicles path optimization on half-open multi depots was used to investigate by branch and bound method and genetic algorithm.The results show that mobile charging vehicles path optimization problem on half-open multi depots is solved 10 times,and the average deviation g ap between the solution obtained in each run and the optimal solution in 10 times is 1.22%,which illustrates the genetic algorithm has good stability.Compared with the independent service mode of single depot,the half-open multi depots joint service can provide more routing choices for mobile charging vehicles,reduce the mileage of charging vehicles and the operating cost of the platform.Compared with the centralized distribution of customer points,the cost saving effect of mobile charging platform is more significant under the random distribution and mixed distribution of customer points.
作者
周长影
张圣忠
陆迪
白雪
ZHOU Chang-ying;ZHANG Sheng-zhong;LU Di;BAI Xue(School of Transportation Engineering,Chang an University,Xi an 710064,China;School of Economics and Management,Chang an University,Xi an 710064,China)
出处
《科学技术与工程》
北大核心
2023年第20期8881-8887,共7页
Science Technology and Engineering
基金
国家自然科学基金(71901037)
陕西省自然科学基金(2020JQ-395)。
关键词
移动充电车
半开放式联合服务
多车场
路径优化
遗传算法
mobile charging vehicles
half-open joint service
multi depots
path optimization
genetic algorithm
