Hybrid Estimation of Distribution PSO and Neural Networks for Bipartite Subgraph Problems

摘要：

Bipartite subgraph problem (BSP) is a classical problem in combinatorial optimization. In this paper we present a new approach to the BSP using hybrid of discrete estimation of distribution particle swarm optimization (DEDPSO) and neural networks. The proposed approach incorporates a chaotic discrete Hopfield neural network (CDHNN), as a local search scheme, into DEDPSO and develops a hybrid algorithm DEDPSO-CDHNN. The proposed algorithm not only performs exploration by using the population-based evolutionary search ability of the DEDPSO, but also performs exploitation by using the CDHNN. Simulation results show that the proposed algorithm has superior ability for bipartite subgraph problem.

关键词： Bipartite subgraph problem particle swarm optimization discrete estimation of distribution discrete Hopfield neural network

作者: Yalan Zhou Jiahai Wang Jian Yin

作者单位: Department of Computer Science, Sun Yat-sen University, No.135, Xingang West Road, Guangzhou 510275, P.R.China

会议类型: 国际会议

会议名称: The Second International Symposium on Intelligence Computation and Applications(ISICA 2007)(第二届智能计算及其应用国际会议)

会议地点: 武汉

会议语种:英文

在线出版日期: 2007-09-21（万方平台首次上网日期，不代表论文的发表时间）