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Journal of Scheduling

, 12:17 | Cite as

A comparison of five heuristics for the multiple depot vehicle scheduling problem

  • Ann-Sophie Pepin
  • Guy Desaulniers
  • Alain Hertz
  • Dennis Huisman
Article

Abstract

Given a set of timetabled tasks, the multi-depot vehicle scheduling problem consists of determining least-cost schedules for vehicles assigned to several depots such that each task is accomplished exactly once by a vehicle. In this paper, we propose to compare the performance of five different heuristics for this well-known problem, namely, a truncated branch-and-cut method, a Lagrangian heuristic, a truncated column generation method, a large neighborhood search heuristic using truncated column generation for neighborhood evaluation, and a tabu search heuristic. The first three methods are adaptations of existing methods, while the last two are new in the context of this problem. Computational results on randomly generated instances show that the column generation heuristic performs the best when enough computational time is available and stability is required, while the large neighborhood search method is the best alternative when looking for good quality solutions in relatively fast computational times.

Keywords

Vehicle scheduling Multiple depot Heuristics Branch-and-cut Column generation Lagrangian heuristic Tabu search Large neighborhood search 

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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Ann-Sophie Pepin
    • 1
  • Guy Desaulniers
    • 2
  • Alain Hertz
    • 2
  • Dennis Huisman
    • 3
  1. 1.Giro Inc.MontrealCanada
  2. 2.Department of Mathematics and Industrial EngineeringÉcole Polytechnique and GERADMontrealCanada
  3. 3.Econometric Institute and ECOPTErasmus University RotterdamRotterdamThe Netherlands

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