A neural network model for finding a near-maximum clique

Nubuo Funabiki, Yoshiyasu Takefuji, Kuo Chun Lee

研究成果: Article査読

27 被引用数 (Scopus)

抄録

A parallel algorithm based on the neural network model for finding a near-maximum clique is presented in this paper. A maximum clique of a graph G is a maximum complete subgraph of G where any two vertices are adjacent. The problem of finding a maximum clique is NP-complete. The parallel algorithm requires n processing elements for an n-vertex graph problem. The algorithm is verified by solving 230 different graph problems. The simulation results show that our computation time on a Macintosh IIfx is shorter than that of two better known algorithms on a Cray 2 and an IBM 3090 while the solution quality is similar. The algorithm solves a near-maximum clique problem in nearly constant time on a parallel machine with n processors.

本文言語English
ページ(範囲)340-344
ページ数5
ジャーナルJournal of Parallel and Distributed Computing
14
3
DOI
出版ステータスPublished - 1992 3
外部発表はい

ASJC Scopus subject areas

  • ソフトウェア
  • 理論的コンピュータサイエンス
  • ハードウェアとアーキテクチャ
  • コンピュータ ネットワークおよび通信
  • 人工知能

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