摘要
乘务排班计划是城市轨道交通运营管理中的重要环节,为了解决目前乘务排班效率低下的问题,对乘务排班计划进行优化。在考虑便乘的情况下,以乘务排班计划总接续时间最小及总运营成本最小为目标建立地铁乘务排班计划编制的双目标优化模型。在满足相关约束条件的基础上,将乘务作业段按照早、白、夜班分成3组,以乘务作业段为顶点,乘务作业段之间的接续关系为弧构建早、白、夜班的网络图,并形成乘务作业段接续时间矩阵,将乘务排班转化为最短路问题。运用相关最短路算法进行求解,该算法采用动态优化逼近的方法,一条最短路径即为一个乘务任务。以成都地铁5号线为例进行乘务排班计划编制,对模型和算法进行测试。研究结果表明:在求得的乘务排班计划中,早班乘务任务个数为53个,任务时长为280 h 34 min 57 s;白班乘务任务个数为41个,任务时长为199 h 54 min 51 s;夜班乘务任务个数为49个,任务时长为215 h 25 min 37 s。总乘务任务个数为143个,总工作时长为695 h 55 min 25 s。与手工编制结果相比,降低了乘务排班计划的总成本及接续时间,提高了求解效率。
Crew scheduling is an important role in urban rail transit operation management.It is optimized in order to solve the problem of low efficiency.In consider of deadheading,subway crew scheduling was studied.A double objective optimization model was established with the shortest connecting time of the crew scheduling and the least cost.As the large number of the crew work-pieces,they were divided into three groups according to the morning,white and night shifts on the basis of constraint condition.And the crew work-pieces were taken as the vertex.The connection relationship of the crew work-pieces was taken as the arc to construct the network diagram of the morning,day and night shifts.The shortest path faster algorithm was used to solve the problem.The algorithm adopted the idea of priority queue,and the shortest path was the crew task.Finally,taking Chengdu Metro Line 5 as an example,the results are as follows.The number of morning crew tasks is 53.The duration of morning crew tasks is 280 h 34 min 57 s.The number of day crew tasks is 41.The duration of day crew tasks is 199 h 54 min 51 s.The number of night crew tasks is 49.The duration of night crew tasks is 215 h 25 min 37 s.The total number of crew tasks is 143.The total duration of crew tasks is 695 h 55 min 25 s in the crew scheduling plan.Compared with manual results,the algorithm reduces the total cost and connecting time and improve the solving efficiency of the crew scheduling.
作者
薛锋
梁鹏
李海
陈崇双
周天星
XUE Feng;LIANG Peng;LI Hai;CHEN Chongshuang;ZHOU Tianxing(School of Transportation and Logistics,Southwest Jiaotong University,Chengdu 611756,China;National United Engineering Laboratory of Integrated and Intelligent Transportation,Chengdu 611756,China;National Engineering Laboratory of Integrated Transportation Big Data Application Technology,Chengdu 611756,China;School of Mathematics,Southwest Jiaotong University,Chengdu 611756,China;Transportation and Urban Planning Institute,China Railway Eryuan Engineering Group Co.,Ltd.,Chengdu 610031,China)
出处
《铁道科学与工程学报》
EI
CAS
CSCD
北大核心
2022年第9期2532-2540,共9页
Journal of Railway Science and Engineering
基金
国家重点研发计划项目(2017YFB1200702)
四川省科技计划项目(2021YJ0077)。
关键词
城市交通
优化模型
SPFA算法
乘务排班计划
网络图
最短路径
urban traffic
optimization model
shortest path faster algorithm
crew scheduling
network diagram
the shortest path
