Off-line and on-line tuning: a study on operator selection for a memetic algorithm applied to the QAP

Authors:
Gianpiero Francesca;Paola Pellegrini;Thomas Stützle;Mauro Birattari
Affiliations:
Dipartimento di Ingegneria, University of Sannio, Benevento, Italy;IRIDIA, CoDE, Université Libre de Bruxelles, Brussels, Belgium;IRIDIA, CoDE, Université Libre de Bruxelles, Brussels, Belgium;IRIDIA, CoDE, Université Libre de Bruxelles, Brussels, Belgium
Venue:
EvoCOP'11 Proceedings of the 11th European conference on Evolutionary computation in combinatorial optimization
Year:
2011

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Abstract

Tuning methods for selecting appropriate parameter configurations of optimization algorithms have been the object of several recent studies. The selection of the appropriate configuration may strongly impact on the performance of evolutionary algorithms. In this paper, we study the performance of three memetic algorithms for the quadratic assignment problem when their parameters are tuned either off-line or on-line. Off-line tuning selects a priori one configuration to be used throughout the whole run for all the instances to be tackled. On-line tuning selects the configuration during the solution process, adapting parameter settings on an instance-per-instance basis, and possibly to each phase of the search. The results suggest that off-line tuning achieves a better performance than on-line tuning.