Ant algorithms for the university course timetabling problem with regard to the state-of-the-art

Authors:
Krzysztof Socha;Michael Sampels;Max Manfrin
Affiliations:
IRIDIA, Université Libre de Bruxelles, Bruxelles, Belgium;IRIDIA, Université Libre de Bruxelles, Bruxelles, Belgium;IRIDIA, Université Libre de Bruxelles, Bruxelles, Belgium
Venue:
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
Year:
2003

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Abstract

Two ant algorithms solving a simplified version of a typical university course timetabling problem are presented -Ant Colony System and MAX-MIN Ant System. The algorithms are tested over a set of instances from three classes of the problem. Results are compared with recent results obtained with several metaheuristics using the same local search routine (or neighborhood definition), and a reference random restart local search algorithm. Further, both ant algorithms are compared on an additional set of instances. Conclusions are drawn about the performance of ant algorithms on timetabling problems in comparison to other metaheuristics. Also the design, implementation, and parameters of ant algorithms solving the university course timetabling problem are discussed. It is shown that the particular implementation of an ant algorithm has significant influence on the observed algorithm performance.