Experimental Algorithms

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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.

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