Chapter
Jun 29, 2016
A Two-Stage Model of Crew Rostering Considering the Balance of Working Intensity for Urban Rail Transit
Authors: Xiaobo Peng, M.S. [email protected], Shaokuan Chen [email protected], Hua Jin, M.S. [email protected], Zhuoran Ma, B.S. [email protected], and Wenzheng Jia, Ph.D. [email protected]Author Affiliations
Publication: CICTP 2016
Abstract
Crew rostering for urban rail transit (URT), whose quality has a significant influence on the operation of URT, plays an important part of URT operational management. This paper takes the balance of working intensity as the objective to obtain a crew roster in a given period, and proposes a mathematical model for crew rostering. The crew rostering model is developed in two stages, which are namely rostering and assignment. The rostering model at the first stage simplifies the problem without any distinction among the type of shifts. Due to the result of the rostering model, the assignment model at the second stage assigns different shifts to specific duties. Finally, this two-stage model is applied to the management of urban rail transportation system in Beijing. The overall crew rostering in the case studies is solved by CPLEX. The result shows that the proposed model and solution method are able to efficiently find a fairer crew rostering plan for URT comparing to the existing plan.
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© 2016 American Society of Civil Engineers.
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Published online: Jun 29, 2016
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The MOE Key Laboratory for Transportation Complex Systems Theory and Technology, Beijing Jiaotong Univ., Beijing 100044. E-mail: [email protected]
Professor, The MOE Key Laboratory for Transportation Complex Systems Theory and Technology, Beijing Jiaotong Univ., Beijing 100044. E-mail: [email protected]
The MOE Key Laboratory for Transportation Complex Systems Theory and Technology, Beijing Jiaotong Univ., Beijing 100044. E-mail: [email protected]
The MOE Key Laboratory for Transportation Complex Systems Theory and Technology, Beijing Jiaotong Univ., Beijing 100044. E-mail: [email protected]
China Urban Sustainable Transport Research Center, China Academy of Transportation Sciences, Beijing 100029. E-mail: [email protected]
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