Automatic Tuning of GRASP with Path-Relinking Heuristics with a Biased Random-Key Genetic Algorithm

• Type: Article in International Conference Proceedings Book
• Date: 2010

Authors

Paola Festa (Author) Other; Jose F Goncalves (Author) FEP; Mauricio G C Resende (Author) Other; Ricardo M A Silva (Author) Other

Conference proceedings International

Title: EXPERIMENTAL ALGORITHMS, PROCEEDINGS

Pages: 338-349

9th International Symposium on Experimental Algorithms

Ischia Isl, ITALY, MAY 20-22, 2010

Indexing

ISI Web of Knowledge - 7 Citations

ISI Web of Science

Scopus - 9 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

CORDIS: Social sciences > Economics > Management studies

Other information

Authenticus ID: P-005-5N3

DOI: 10.1007/978-3-642-13193-6_29

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12