GRASP with path-relinking (GRASP+PR) is a metaheuristic for finding optimal or near-optimal solutions of combinatorial optimization problems. This paper proposes a new automatic parameter tuning procedure for GRASP+PR heuristics based on a biased random-key genetic algorithm (BRKGA). Given a GRASP+PR heuristic with n input parameters, the tuning procedure makes use of a BRKGA in a first phase to explore the parameter space and set the parameters with which the GRASP+PR heuristic will run in a second phase. The procedure is illustrated with a GRASP+PR for the generalized quadratic assignment problem with n = 30 parameters. Computational results show that the resulting hybrid heuristic is robust. © Springer-Verlag Berlin Heidelberg 2010.
CITATION STYLE
Festa, P., Goņcalves, J. F., Resende, M. G. C., & Silva, R. M. A. (2010). Automatic tuning of GRASP with path-relinking heuristics with a biased random-key genetic algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6049 LNCS, pp. 338–349). https://doi.org/10.1007/978-3-642-13193-6_29
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