A memetic algorithm with genetic particle swarm optimization and neural network for maximum cut problems

Authors:
Jiahai Wang
Affiliations:
Department of Computer Science, Sun Yat-sen University, Guangzhou, P.R.China
Venue:
LSMS'07 Proceedings of the Life system modeling and simulation 2007 international conference on Bio-Inspired computational intelligence and applications
Year:
2007

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Abstract

In this paper, we incorporate a chaotic discrete Hopfield neural network (CDHNN), as a local search scheme, into a genetic particle swarm optimization (GPSO) and develop a memetic algorithm GPSO-CDHNN for the maximum cut problem. The proposed algorithm not only performs exploration by using the population-based evolutionary search ability of the GPSO, but also performs exploitation by using the CDHNN. Simulation results show that the proposed algorithm has superior ability for maximum cut problems.