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Two-level decomposition algorithm for crew rostering problems with fair working condition

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  • Nishi, Tatsushi
  • Sugiyama, Taichi
  • Inuiguchi, Masahiro

Abstract

A typical railway crew scheduling problem consists of two phases: a crew pairing problem to determine a set of crew duties and a crew rostering problem. The crew rostering problem aims to find a set of rosters that forms workforce assignment of crew duties and rest periods satisfying several working regulations. In this paper, we present a two-level decomposition approach to solve railway crew rostering problem with the objective of fair working condition. To reduce computational efforts, the original problem is decomposed into the upper-level master problem and the lower-level subproblem. The subproblem can be further decomposed into several subproblems for each roster. These problems are iteratively solved by incorporating cuts into the master problem. We show that the relaxed problem of the master problem can be formulated as a uniform parallel machine scheduling problem to minimize makespan, which is NP-hard. An efficient branch-and-bound algorithm is applied to solve the master problem. Effective valid cuts are developed to reduce feasible search space to tighten the duality gap. Using data provided by the railway company, we demonstrate the effectiveness of the proposed method compared with that of constraint programming techniques for large-scale problems through computational experiments.

Suggested Citation

  • Nishi, Tatsushi & Sugiyama, Taichi & Inuiguchi, Masahiro, 2014. "Two-level decomposition algorithm for crew rostering problems with fair working condition," European Journal of Operational Research, Elsevier, vol. 237(2), pages 465-473.
    • Handle: RePEc:eee:ejores:v:237:y:2014:i:2:p:465-473
    DOI: 10.1016/j.ejor.2014.02.010
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    Cited by:

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    3. Breugem, T. & Dollevoet, T.A.B. & Huisman, D., 2017. "Is Equality always desirable?," Econometric Institute Research Papers EI2017-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Doi, Tsubasa & Nishi, Tatsushi & Voß, Stefan, 2018. "Two-level decomposition-based matheuristic for airline crew rostering problems with fair working time," European Journal of Operational Research, Elsevier, vol. 267(2), pages 428-438.
    5. Mesquita, Marta & Moz, Margarida & Paias, Ana & Pato, Margarida, 2015. "A decompose-and-fix heuristic based on multi-commodity flow models for driver rostering with days-off pattern," European Journal of Operational Research, Elsevier, vol. 245(2), pages 423-437.
    6. F. Zeynep Sargut & Caner Altuntaş & Dilek Cetin Tulazoğlu, 2017. "Multi-objective integrated acyclic crew rostering and vehicle assignment problem in public bus transportation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1071-1096, October.
    7. Thomas Breugem & Twan Dollevoet & Dennis Huisman, 2022. "Is Equality Always Desirable? Analyzing the Trade-Off Between Fairness and Attractiveness in Crew Rostering," Management Science, INFORMS, vol. 68(4), pages 2619-2641, April.
    8. Thomas Breugem & Luk N. Van Wassenhove, 2022. "The Price of Imposing Vertical Equity Through Asymmetric Outcome Constraints," Management Science, INFORMS, vol. 68(11), pages 7977-7993, November.
    9. Breugem, Thomas & Van Wassenhove, Luk N., 2022. "The price of imposing vertical equity through asymmetric outcome constraints," Other publications TiSEM b6e85652-c54a-4597-a32e-d, Tilburg University, School of Economics and Management.

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