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Bidline scheduling with equity by heuristic dynamic constraint aggregation

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  • Boubaker, Khaled
  • Desaulniers, Guy
  • Elhallaoui, Issmail

Abstract

The bidline scheduling problem with equity arises in several North American airlines. It consists of determining anonymous monthly schedules, called bidlines, that will be subsequently assigned to the crew members according to their bids and seniority. These bidlines must satisfy safety and collective agreement rules. Furthermore, to ensure an equity between the employees, each bidline should have as much as possible the same number of days off and the same number of credited (paid) hours. In this paper, we propose an approximate set partitioning type formulation for this problem and two heuristics for solving it. The first one is a standard branch-and-price heuristic that relies on a rounding procedure to derive integer solutions. The second one is obtained by combining this first heuristic with a dynamic constraint aggregation method that was recently proposed in the literature. Computational results show that, for the largest tested instances, the dynamic constraint aggregation heuristic can produce better quality solutions in a fraction of the computational time required by the standard branch-and-price heuristic.

Suggested Citation

  • Boubaker, Khaled & Desaulniers, Guy & Elhallaoui, Issmail, 2010. "Bidline scheduling with equity by heuristic dynamic constraint aggregation," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 50-61, January.
  • Handle: RePEc:eee:transb:v:44:y:2010:i:1:p:50-61
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    References listed on IDEAS

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    Cited by:

    1. Saddoune, Mohammed & Desaulniers, Guy & Elhallaoui, Issmail & Soumis, François, 2011. "Integrated airline crew scheduling: A bi-dynamic constraint aggregation method using neighborhoods," European Journal of Operational Research, Elsevier, vol. 212(3), pages 445-454, August.
    2. Philippe Racette & Frédéric Quesnel & Andrea Lodi & François Soumis, 2024. "Gaining insight into crew rostering instances through ML-based sequential assignment," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(3), pages 537-578, October.
    3. Quesnel, Frédéric & Desaulniers, Guy & Soumis, François, 2020. "A branch-and-price heuristic for the crew pairing problem with language constraints," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1040-1054.
    4. Mohammed Saddoune & Guy Desaulniers & Issmail Elhallaoui & François Soumis, 2012. "Integrated Airline Crew Pairing and Crew Assignment by Dynamic Constraint Aggregation," Transportation Science, INFORMS, vol. 46(1), pages 39-55, February.
    5. Liang, Zhe & Feng, Yuan & Zhang, Xiaoning & Wu, Tao & Chaovalitwongse, Wanpracha Art, 2015. "Robust weekly aircraft maintenance routing problem and the extension to the tail assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 238-259.
    6. Vahid Zeighami & François Soumis, 2019. "Combining Benders’ Decomposition and Column Generation for Integrated Crew Pairing and Personalized Crew Assignment Problems," Transportation Science, INFORMS, vol. 53(5), pages 1479-1499, September.
    7. Atoosa Kasirzadeh & Mohammed Saddoune & François Soumis, 2017. "Airline crew scheduling: models, algorithms, and data sets," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(2), pages 111-137, June.

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