摘要
针对电动公交车辆调度问题,提出一种基于文化基因算法的车辆调度方法.首先,设计了初始个体生成算法用来构造初始种群;然后,设计了一种针对公交车辆调度问题的交叉操作用于全局搜索,改进了3种邻域搜索算子,并将其与已有的邻域搜索算子结合用于局部搜索.最后,设计了一种基于车辆块的评价函数,用于引导邻域搜索算子进行搜索.将该方法用于某市的实际三条公交线路,结果表明:与人工调度方案相比,该方法可减少1~7辆车,提高平均车辆利用率,运行时间小于15 s.
Aiming at electric bus scheduling problem,a cultural genetic algorithm based vehicle scheduling approach was proposed.First,initial individual generation algorithms were devised to construct the initial population.Then,a crossover operation for the bus scheduling problem was designed to perform global search. Furthermore,three kinds of neighborhood search operators were improved,and combined with the existing neighborhood search operators to perform local search.An evaluation function based on vehicle blocks was devised to guide the neighborhood search operators for searching.The approach was applied to three actual bus lines in a city.Experimental results show that compared with the manual scheduling scheme,the approach can reduce 1~7 vehicles and increase the average vehicle utilization rate,and its running time is less than 15 s.
作者
王春露
聂少康
左兴权
于芷琦
WANG Chunlu;NIE Shaokang;ZUO Xingquan;YU Zhiqi(School of Cyberspace Security,Beijing University of Posts and Telecommunications,Beijing 100876,China;School of Computer Science,Beijing University of Posts and Telecommunications,Beijing 100876,China;Department of Mathematical Science,Xi'an Jiaotong-Liverpool University,Suzhou 215123,Jiangsu China)
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2022年第1期7-12,共6页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(61873040)
国家重点研发计划资助项目(A09B01C02-201801D2)。
关键词
电动公交车
车辆调度
文化基因算法
邻域搜索
评价函数
electric bus
bus scheduling
memetic algorithm
neighborhood search
evaluation function
