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 randomkey 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.
Automatic tuning of GRASP with path-relinking heuristics with a biased random-key genetic algorithm / Festa, Paola; J. F., Goncalves; M. G. C., Resende; R. M. A., Silva. - 6049:(2010), pp. 338-349. [10.1007/978-3-642-13193-6_29]
Automatic tuning of GRASP with path-relinking heuristics with a biased random-key genetic algorithm
FESTA, PAOLA;
2010
Abstract
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 randomkey 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
