New variable depth local search for multiple depot vehicle scheduling problems

Tomoshi Otsuki () and Kazuyuki Aihara
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Tomoshi Otsuki: Toshiba Corporation
Kazuyuki Aihara: The University of Tokyo

Journal of Heuristics, 2016, vol. 22, issue 4, No 10, 567-585

Abstract: Abstract The multiple depot vehicle scheduling problem (MDVSP) is a well-known and important NP-hard problem in transport scheduling. In this study, we first provide an original interpretation of the search space of the MDVSP. Next, we present a local search algorithm which utilizes pruning and deepening techniques in the variable depth search framework. Computational results using well-known test cases show that our method achieves better results than the second-best local search based method does by 8.6–30.1 %, and exhibits the best short-term performance among the state-of-the-art methods.

Keywords: Vehicle scheduling; Variable depth search; Large neighborhood search (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10732-014-9264-z

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