Submitted to 9th International Symposium on Experimental Algorithms (SEA 2010)
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+P 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.
PDF file of full paper
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