摘要
面临环境保护和城市物流配送的需求,电动车已成为替代传统燃油车的交通工具,路径规划是电动车配送问题的关键技术之一。在传统车辆路径问题基础上,考虑城市路网交通的时变性、在途充电排队、充电决策、多车型等影响因素,以配送总成本最小为目标,建立了时变路网下的多车型电动车车辆路径优化模型,并设计了一种改进遗传算法。仿真结果表明,本文方法可以让电动车在配送过程中有效规避交通拥堵,合理调度车辆,降低总配送成本。
Considering the problems of urban environmental protection and urban logistics distribution needs,electric vehicles(EVs),an ideal means of transportation to replace conventional fuel vehicles have been used to solve the urban logistics distribution needs and environmental protection problems.Route planning is one of the focal problems of urban distribution using EVs.On the basis of the traditional Vehicle Routing Problem(VRP),this study considers influential factors such as the time-varying characteristics of urban road networks,in-route charging queuing,charging decisions,and multi-type vehicles.With the goal of minimizing the total distribution cost,an optimization model for the multi-type electric vehicle routing problem under time-varying road networks is established.Moreover,an improved genetic algorithm is designed.Simulation test results show that the proposed method can allow EVs to effectively avoid traffic congestion during the distribution process,optimize reasonably vehicle scheduling and reduce the total distribution cost.
作者
赵志学
蔡晨光
ZHAO Zhi-xue;CAI Chen-guang(School of Computer Science,Hunan University of Technology and Business,Changsha 410205,China;School of Accounting,Hunan University of Finance and Economics,Changsha 410205,China)
出处
《价值工程》
2026年第7期66-70,共5页
Value Engineering
基金
湖南省自然科学基金(2022JJ30219)
湖南省教育厅科学研究项目优秀青年基金(22B0631)
湖南省教育厅科学研究重点项目(23A0679)
湖南省社会科学成果评审委员会课题(XSP25YBC671)
湖南省社会科学项目(25YBA314)。
关键词
时变路网
多车型
改进遗传算法
time-varying network traffic
multi-model
improved genetic algorithm
