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A comparison of the performance of different metaheuristics on the timetabling problem.

Rossi-Doria, Olivia; Sampels, Michael; Birattari, Mauro; Chiarandini, Marco; Dorigo, Marco; Gambardella, Luca Maria; Knowles, Joshua; Manfrin, Max; Mastrolilli, Monaldo; Paechter, Ben; Paquete, Luis; Stutzle, Thomas

Authors

Olivia Rossi-Doria

Michael Sampels

Mauro Birattari

Marco Chiarandini

Marco Dorigo

Luca Maria Gambardella

Joshua Knowles

Max Manfrin

Monaldo Mastrolilli

Luis Paquete

Thomas Stutzle



Contributors

Edmund Burke
Editor

P Causmaecker
Editor

Abstract

The main goal of this paper is to attempt an unbiased comparison of the performance of straightforward implementations of five different metaheuristics on a university course timetabling problem. In particular, the metaheuristics under consideration are Evolutionary Algorithms, Ant Colony Optimization, Iterated Local Search, Simulated Annealing, and Tabu Search. To attempt fairness, the implementations of all the algorithms use a common solution representation, and a common neighbourhood structure or local search. The results show that no metaheuristic is best on all the timetabling instances considered. Moreover, even when instances are very similar, from the point of view of the instance generator, it is not possible to predict the best metaheuristic, even if some trends appear when focusing on particular instance classes. These results underline the difficulty of finding the best metaheuristics even for very restricted classes of timetabling problem.

Citation

Rossi-Doria, O., Sampels, M., Birattari, M., Chiarandini, M., Dorigo, M., Gambardella, L. M., Knowles, J., Manfrin, M., Mastrolilli, M., Paechter, B., Paquete, L., & Stutzle, T. (2002, August). A comparison of the performance of different metaheuristics on the timetabling problem

Start Date Aug 21, 2002
End Date Aug 23, 2002
Publication Date 2003-08
Deposit Date May 11, 2010
Peer Reviewed Peer Reviewed
Volume 2740
Pages 329-351
Book Title Practice and Theory of AutomatedTimetabling IV
ISBN 978-3-540-40699-0
DOI https://doi.org/10.1007/978-3-540-45157-0_22
Keywords university timetabling; evolutionary algorithms; ant colony optimization; iterated local search; simulated annealing; tabu search;
Public URL http://researchrepository.napier.ac.uk/id/eprint/3348
Publisher URL http://dx.doi.org/10.1007/978-3-540-45157-0_22