摘要
针对电动货车路径优化问题,应用物流网络以及电动货车电量消耗等方面的知识,研究了电动货车的智能调度方法,构建了带时间窗的电动货车路径优化模型(electric vehicle routing problem with time window,EVRPTW)。该模型考虑了耗电量与电动货车行驶速度、载重量之间的关系,客户满意度与软时间窗之间的关系。同时,引入了计算机智能算法,充分利用了遗传算法、头脑风暴算法等优化算法的智能化特征,有效提高了电动货车的配送效率。仿真结果表明:该模型运用头脑风暴算法的最优值精确度和收敛速度都优于遗传算法,可以有效解决EVRPTW问题。所提出的模型和算法能明显提高配送中心的配送效率,节省充电成本,提高顾客满意度。针对配送中心电动货车运营调度管理的特点,借助计算机技术以及自动控制技术,进一步提高了电动货车的配送效率,为物流网络系统的智能化调度提供技术准备。
Aiming at the problem of electric vehicle routing optimization,applying the knowledge of logistics network and electric vehicle power consumption,we study the intelligent dispatching method of electric trucks and construct an electric vehicle path optimization model with time window(EVRPTW).The relationship between power consumption and the speed and load capacity of electric trucks,and the relationship between customer satisfaction and soft time windows are considered in this model.At the same time,the computer intelligent algorithm is introduced and the intelligent features of the optimization algorithms such as genetic algorithm and brainstorming algorithm are fully applied,which effectively improves the distribution efficiency of electric trucks.The simulation shows that the optimal accuracy and convergence speed of the model using the brainstorming algorithm are better than that of genetic algorithm,which can effectively solve the EVRPTW problem.The proposed model and algorithm can significantly improve the distribution efficiency of the distribution center,save charging costs and improve customer satisfaction.According to the characteristics of operation and dispatch management of electric trucks in distribution center,computer technology and automatic control technology are used to further improve the distribution efficiency of electric trucks and provide technical preparation for intelligent dispatch of logistics network systems.
作者
齐元豪
王凯
付亚平
QI Yuan-hao;WANG Kai;FU Ya-ping(School of Electrical Engineering,Qingdao University,Qingdao 266000,China)
出处
《计算机技术与发展》
2020年第4期74-78,共5页
Computer Technology and Development
基金
国家自然科学基金青年科学基金项目(61703220)。
关键词
物流网络
计算机智能调度
优化算法
EVRPTW
头脑风暴算法
logistics network
computer intelligent scheduling
optimization algorithm
EVRPTW
brainstorming algorithm
