A Hybrid of Particle Swarm Optimization and Hopfield Networks for Bipartite Subgraph Problems

Authors:
Jiahai Wang
Affiliations:
Department of Computer Science, Sun Yat-sen University, No.135, Xingang West Road, Guangzhou 510275, P.R. China
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Year:
2007

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Abstract

The bipartite subgraph problem is a classical problem in combinatorial optimization. In this paper, we incorporate a chaotic discrete Hopfield neural network (CDHNN), as a local search scheme, into the discrete particle swarm optimization (DPSO) and develop a hybrid algorithm DPSO-CDHNN for the bipartite subgraph problem. The proposed algorithm not only performs exploration by using the population-based evolutionary search ability of the DPSO, but also performs exploitation by using the CDHNN. Simulation results show that the proposed algorithm has superior ability for bipartite subgraph problem.