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Fairness in optimizing bus-crew scheduling process

Author

Listed:
  • Jihui Ma
  • Cuiying Song
  • Avishai (Avi) Ceder
  • Tao Liu
  • Wei Guan

Abstract

This work proposes a model considering fairness in the problem of crew scheduling for bus drivers (CSP-BD) using a hybrid ant-colony optimization (HACO) algorithm to solve it. The main contributions of this work are the following: (a) a valid approach for cases with a special cost structure and constraints considering the fairness of working time and idle time; (b) an improved algorithm incorporating Gamma heuristic function and selecting rules. The relationships of each cost are examined with ten bus lines collected from the Beijing Public Transport Holdings (Group) Co., Ltd., one of the largest bus transit companies in the world. It shows that unfair cost is indirectly related to common cost, fixed cost and extra cost and also the unfair cost approaches to common and fixed cost when its coefficient is twice of common cost coefficient. Furthermore, the longest time for the tested bus line with 1108 pieces, 74 blocks is less than 30 minutes. The results indicate that the HACO-based algorithm can be a feasible and efficient optimization technique for CSP-BD, especially with large scale problems.

Suggested Citation

  • Jihui Ma & Cuiying Song & Avishai (Avi) Ceder & Tao Liu & Wei Guan, 2017. "Fairness in optimizing bus-crew scheduling process," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-19, November.
    • Handle: RePEc:plo:pone00:0187623
    DOI: 10.1371/journal.pone.0187623
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    References listed on IDEAS

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    1. S Fores & L Proll & A Wren, 2002. "TRACS II: a hybrid IP/heuristic driver scheduling system for public transport," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(10), pages 1093-1100, October.
    2. Ma, Xiaolei & Liu, Congcong & Wen, Huimin & Wang, Yunpeng & Wu, Yao-Jan, 2017. "Understanding commuting patterns using transit smart card data," Journal of Transport Geography, Elsevier, vol. 58(C), pages 135-145.
    3. Li, Jingpeng & Kwan, Raymond S. K., 2003. "A fuzzy genetic algorithm for driver scheduling," European Journal of Operational Research, Elsevier, vol. 147(2), pages 334-344, June.
    4. Shen, Yindong & Peng, Kunkun & Chen, Kai & Li, Jingpeng, 2013. "Evolutionary crew scheduling with adaptive chromosomes," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 174-185.
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    Cited by:

    1. Rusul Abduljabbar & Hussein Dia & Sohani Liyanage & Saeed Asadi Bagloee, 2019. "Applications of Artificial Intelligence in Transport: An Overview," Sustainability, MDPI, vol. 11(1), pages 1-24, January.
    2. Jing Wang & Heqi Wang & Ande Chang & Chen Song, 2022. "Collaborative Optimization of Vehicle and Crew Scheduling for a Mixed Fleet with Electric and Conventional Buses," Sustainability, MDPI, vol. 14(6), pages 1-17, March.

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