基于地铁乘务资源共享的排班计划优化方法

针对不同线路间列车不跨线情况下的乘务基地和乘务员共享问题开展研究,分析乘务资源共享,在传统排班模型基础上考虑乘务员跨线值乘,班次出退勤地点比例及其鲁棒性优化,建立乘务排班计划集合覆盖模型.针对乘务资源共享后多线协同优化引起的问题规模显著增大,以连续值乘区段为最小值乘任务单元构建网络图,引入分层结构,多级的汇点和源点,以...

Crew Schedule Optimization for Urban Rail Transit with Crew Resources Sharing

This study aims to address a crew scheduling problem with shared crew members and bases among different lines without considering cross- line trains. Through the analysis on crew resources sharing, a new set covering model for the crew scheduling problem is proposed. Three crucial elements are covered in this model, including the across- line duties, proportion of shifts with different starting and ending locations, and robustness optimization. However, the scale of problem increases dramatically due to the collaborative optimization of shifts among different lines. A network model is developed where consecutive tasks executed by the same train are served as the minimum duty unit. Several improvements are made to satisfy the feasibility constraints of shifts including employing multilayer structure, multilevel source and sink nodes as well as cross-line meal and rest arcs. Furthermore, networks are generated into some sets corresponding to different starting and ending locations. A column generation algorithm is then designed in which the pricing problem is converted into the shortest path problems base on each network set. The experimental results indicate that the crew resources sharing can provide more choice for drivers to select a preferred location when they start and end their daily work. It also significantly reduces the commuting time. Besides, crew resources sharing is able to decrease the shift number by a little and improve the efficiency of crew scheduling.