Paper Info
Title
Automatic tuning of GRASP with path-relinking heuristics with a biased random-key genetic algorithm
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 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.
Year
DOI
Venue
2010
10.1007/978-3-642-13193-6_29
SEA
Keywords
Field
DocType
computational result,combinatorial optimization problem,hybrid heuristic,n input parameter,generalized quadratic assignment problem,tuning procedure,path-relinking heuristics,new automatic parameter,near-optimal solution,pr heuristic,automatic tuning,random-key genetic algorithm,parameter space,combinatorial optimization,algorithm engineering,genetic algorithm,quadratic assignment problem
Mathematical optimization,Heuristic,GRASP,Computer science,Quadratic assignment problem,Combinatorial optimization,Heuristics,Parameter space,Genetic algorithm,Metaheuristic
Conference
Volume
ISSN
ISBN
6049
0302-9743
3-642-13192-1
Citations 
PageRank 
References 
5
0.41
8
Authors
4
Name
Order
Citations
PageRank
Paola Festa128725.32
José F. Gonçalves2100.86
Mauricio G. C. Resende33729336.98
Ricardo M. A. Silva4659.02