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Metaheuristics approach for solving personalized crew rostering problem in public bus transit

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Abstract

The crew rostering problem in public bus transit aims at constructing personalized monthly schedules for all drivers. This problem is often formulated as a multi-objective optimization problem, since it considers the interests of both the management of bus companies and the drivers. Therefore, this paper attempts to solve the multi-objective crew rostering problem with the weighted sum of all objectives using ant colony optimization, simulated annealing, and tabu search methods. To the best of our knowledge, this is the first paper that attempts to solve the personalized crew rostering problem in public transit using different metaheuristics, especially the ant colony optimization. The developed algorithms are tested on numerical real-world instances, and the results are compared with ones solved by commercial solvers.

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Authors and Affiliations

  1. Leuphana University of Lüneburg, Scharnhorststr. 1, 21335, Lüneburg, Germany

    Lin Xie

  2. University of Paderborn, Warburger Str. 100, 33098, Paderborn, Germany

    Marius Merschformann & Leena Suhl

  3. Freie Universität Berlin, Garystr. 21, 14195, Berlin, Germany

    Natalia Kliewer

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  1. Lin Xie
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  2. Marius Merschformann
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  3. Natalia Kliewer
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  4. Leena Suhl
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Correspondence to Lin Xie.

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Xie, L., Merschformann, M., Kliewer, N. et al. Metaheuristics approach for solving personalized crew rostering problem in public bus transit. J Heuristics 23, 321–347 (2017). https://doi.org/10.1007/s10732-017-9348-7

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  • DOI: https://doi.org/10.1007/s10732-017-9348-7

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