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

Lin Xie (), Marius Merschformann, Natalia Kliewer and Leena Suhl
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Lin Xie: Leuphana University of Lüneburg
Marius Merschformann: University of Paderborn
Natalia Kliewer: Freie Universität Berlin
Leena Suhl: University of Paderborn

Journal of Heuristics, 2017, vol. 23, issue 5, No 2, 347 pages

Abstract: 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.

Keywords: Ant colony optimization; Simulated annealing; Tabu search; Crew rostering problem; Personalized/non-cyclic rostering; Public transport (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10732-017-9348-7

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