交通运输系统工程与信息 ›› 2016, Vol. 16 ›› Issue (4): 159-164.

• 系统工程理论与方法 • 上一篇    下一篇

铁路客运乘务排班计划编制模型及算法

杨国元1,史天运*2,张秋亮2   

  1. 1. 中国铁道科学研究院,北京100081;2. 中国铁道科学研究院电子计算技术研究所,北京100081
  • 收稿日期:2016-02-19 修回日期:2016-04-22 出版日期:2016-08-25 发布日期:2016-08-26
  • 作者简介:杨国元(1982-),男,甘肃武威人,博士生.
  • 基金资助:

    铁道部科技研究开发计划项目/Ministry of Railways Science and Technology Research and Development Program (2011X014-D);中国铁道科学研究院基金项目/Fund Project of China Academy of Railway Sciences (2010YJ07).

Model and Algorithm for Railway Passenger Crew Rostering Plan

YANG Guo-yuan1, SHI Tian-yun2, ZHANG Qiu-liang2   

  1. 1. China Academy of Railway Sciences, Beijing 100081, China;2. Institute of Computing Technologies, China Academy of Railway Sciences, Beijing 100081, China
  • Received:2016-02-19 Revised:2016-04-22 Online:2016-08-25 Published:2016-08-26

摘要:

针对铁路客运部门对乘务排班计划编制的问题,分析了车次、交路、乘务员、乘务工时之间的关系.在已知乘务员标准月度乘务工时的前提下,以交路和乘务工时为主要约束条件,以减少乘务班组、降低乘务费用为优化目标,建立客运乘务排班计划编制模型.根据车次之间到发站、到发时间的接续关系,求解符合乘务工时的车次与交路匹配的可行性路径集合,以该集合为基础,提出了求解模型,并设计了基于遗传算法的模型求解算法.通过对某一客运段的车次、班组数据进行算例分析,仿真实验,验证了所提出模型和设计算法可有效解决客运乘务排班计划的编制问题,可降低乘务费用.

关键词: 信息技术, 铁路客运, 乘务排班计划, 乘务交路, 遗传算法

Abstract:

For the question of the crew rostering planning of railway passenger transport department, it is analyzed the relationship of the trains, train routes, crews, and crew working hours. On the premise of known the standard monthly crew working hours, a crew rostering plan model is built for railway passenger transport department. The model is based on the constraints of train routes and crew working hours. The optimization objective of the model is to reduce crew team and crew cost. According to the train connection relationship between arriving station and departing station and between arriving time and departing time, the feasible paths set of matching trains and train routes of meeting crew working hours is solved. Based on this set, the solving model is proposed and the solving algorithm based on genetic algorithm is designed in this paper. By analyzing and stimulating an example of trains and crew teams of a passenger department, it shows that the proposed model and designed algorithm can effectively solve the problem of passenger transport crew rostering planning and reduce crew cost.

Key words: information technology, railway passenger, crew scheduling plan, crew routing, genetic algorithms

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