Template-Type: ReDIF-Paper 1.0
Author-Name: Pepin, A.S.
Author-Name-Last: Pepin
Author-Name: Desaulniers, G.
Author-Name-Last: Desaulniers
Author-Name-First: Guy
Author-Name: Hertz, A.
Author-Name-Last: Hertz
Author-Name-First: Alain
Author-Name: Huisman, D.
Author-Name-Last: Huisman
Author-Name-First: Dennis
Author-Person: phu27
Title: Comparison of heuristic approaches for the multiple depot vehicle scheduling problem
Abstract: Given a set of timetabled tasks, the multi-depot vehicle scheduling problem is a well-known problem that 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 heuristic approaches for this problem, namely, a heuristic \\mip solver, a Lagrangian heuristic, a column generation heuristic, a large neighborhood search heuristic using column generation for neighborhood evaluation, and a tabu search heuristic. The first three methods are adaptations of existing methods, while the last two are novel approaches for 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 a compromise between computational time and solution quality.
Creation-Date: 2006-11-07
File-URL: https://repub.eur.nl/pub/8069/ei200634.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI 2006-34
Keywords: Lagrangian heuristic, column generation, heuristics, large neighborhood search, multiple depot, tabu search, vehicle scheduling
Handle: RePEc:ems:eureir:8069