Enhancing the performance of memetic algorithms by using a matching-based recombination algorithm

Authors:
Regina Berretta;Carlos Cotta;Pablo Moscato
Affiliations:
School of Electrical Engineering and Computer Science, Faculty of Engineering and Built Environment, The University of Newcastle, Callaghan, 2308 NSW, Australia;Departamento de Lenguajes y Ciencias de la Computación, ETSI Informática (3.2.49), Universidad de Málaga, Campus de Teatinos, 29071 - Málaga, Spain;School of Electrical Engineering and Computer Science, Faculty of Engineering and Built Environment, The University of Newcastle, Callaghan, 2308 NSW, Australia
Venue:
Metaheuristics
Year:
2004

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Abstract

The NUMBER PARTITIONING PROBLEM (MNP) remains as one of the simplest-to-describe yet hardest-to-solve combinatorial optimization problems. In this paper we use the MNP as a surrogate for several related real-world problems, to test new heuristics ideas. To be precise, we study the use of weight-matching techniques to devise smart memetic operators. Several options are considered and evaluated for that purpose. The positive computational results indicate that - despite the MNP may be not the best scenario for exploiting these ideas - the proposed operators can be really promising tools for dealing with more complex problems of the same family.