基于遗传禁忌算法的城市轨道交通乘务任务配对研究  

Research on Urban Rail Transit Crew Task Pairing Based on Genetic Tabu Algorithm

作　　者：薛锋[1,2,3] 李海 梁鹏 陈崇双[4] 罗建 XUE Feng;LI Hai;LIANG Peng;CHEN Chongshuang;LUO Jian(School of Transportation and Logistics,Southwest Jiaotong University,Chengdu 611756,Sichuan,China;National United Engineering Laboratory of Integrated and Intelligent Transportation,Southwest Jiaotong University,Chengdu 611756,Sichuan,China;National Engineering Laboratory of Application Technology of Integrated Transportation Big Data,Southwest Jiaotong University,Chengdu 611756,Sichuan,China;School of Mathematics,Southwest Jiaotong University,Chengdu 611756,Sichuan,China;School of Transportation and Automotive Engineering,Xihua University,Chengdu 610039,Sichuan,China)

机构地区：[1]西南交通大学交通运输与物流学院,四川成都611756 [2]西南交通大学综合交通运输智能化国家地方联合工程实验室,四川成都611756 [3]西南交通大学综合交通大数据应用技术国家工程实验室,四川成都611756 [4]西南交通大学数学学院,四川成都611756 [5]西华大学汽车与交通学院,四川成都610039

出　　处：《铁道运输与经济》2022年第7期103-109,118,共8页Railway Transport and Economy

基　　金：国家重点研发计划(2017YFB1200702);四川省科技计划项目(2021YJ0077)。

摘　　要：为提高城市轨道交通乘务员值乘效率并降低运营支出,研究不同时间参数设置下的乘务任务配对问题,综合考虑乘务员连续工作时间、班次交替时刻、各班次最长工作时间、休息时间、用餐时间等约束,以最大化一日内所有乘务员的值乘效率为目标,建立非线性混合整数规划模型,并设计遗传禁忌混合搜索算法进行求解,从而得到最优参数设置方案和相应的乘务排班计划。以成都地铁5号线一日内运行图数据为基础,结合既有文献参数设置方案进行验证,算例结果表明,不同参数设置会不同程度影响乘务计划效率,特别是相邻乘务作业段间的休息时间,同时提出的方法只需要迭代27次就可以获得较优解,最优乘务任务效率为0.836 1,明显优于代入既有文献参数获得的乘务计划效率。To improve crews’ efficiency on duty and reduce operating expenses of the urban rail transit, this paper studied the crew task pairing under different time parameter settings and comprehensively considered the constraints such as crews’ continuous working hours, rotating shift time, maximum working hours of each shift, break time, and dining time. In addition, this paper established a nonlinear mixed integer programming model to maximize crews’ efficiency on duty in a day,designed a genetic-tabu hybrid search algorithm to solve the model, and obtained the optimal parameter setting scheme and the corresponding crew scheduling. On the basis of the operating data of Chengdu Metro Line 5 in a day, the proposed scheme was verified by combining parameter setting schemes in the existing literature. The results show that different parameter settings can affect crews’ efficiency on duty to varying degrees, especially the break time between adjacent crew operations. At the same time, it is found that the proposed scheme can obtain the optimal solution through only 27 iterations, and the optimal crew task efficiency is 0.836 1, which is significantly better than that obtained with parameters in the existing literature.

关 键 词：城市轨道交通 乘务任务配对 遗传禁忌搜索算法 混合整数规划 参数设置 

分 类 号：U293.5[交通运输工程—交通运输规划与管理]