An improved optimal competitive Hopfield network for bipartite subgraph problems

Jiahai Wang; Zheng Tang

doi:10.1016/j.neucom.2004.03.012

An improved optimal competitive Hopfield network for bipartite subgraph problems

Jiahai Wang^*, Zheng Tang

^*この論文の責任著者

工学科　知能情報工学コース

研究成果: ジャーナルへの寄稿 › 学術論文 › 査読

16 被引用数 (Scopus)

抄録

The bipartite subgraph problem is a classical problem in combinatorial optimization. Recently, Galán-Marín et al. proposed an optimal competitive Hopfield model (OCHOM) for this problem. In this paper, we propose a new algorithm that permits temporary energy increases and includes stochastic dynamics. The new algorithm helps the OCHOM escape from local minima. A number of instances have been simulated to verify the proposed algorithm.

本文言語	英語
ページ（範囲）	413-419
ページ数	7
ジャーナル	Neurocomputing
巻	61
号	1-4
DOI	https://doi.org/10.1016/j.neucom.2004.03.012
出版ステータス	出版済み - 2004/10

ASJC Scopus 主題領域

コンピュータサイエンスの応用
認知神経科学
人工知能

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10.1016/j.neucom.2004.03.012

引用スタイル

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keywords = "Bipartite subgraph problem, Hill-climbing dynamics, Optimal competitive Hopfield model",

author = "Jiahai Wang and Zheng Tang",

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AB - The bipartite subgraph problem is a classical problem in combinatorial optimization. Recently, Galán-Marín et al. proposed an optimal competitive Hopfield model (OCHOM) for this problem. In this paper, we propose a new algorithm that permits temporary energy increases and includes stochastic dynamics. The new algorithm helps the OCHOM escape from local minima. A number of instances have been simulated to verify the proposed algorithm.

KW - Bipartite subgraph problem

KW - Hill-climbing dynamics

KW - Optimal competitive Hopfield model

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An improved optimal competitive Hopfield network for bipartite subgraph problems

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