A neural network parallel algorithm for clique vertex-partition problems

Nobuo Funabiki, Yoshiyasu Takefuji, Kuo Chun Lee, Yong Beom Cho

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


A parallel algorithm based on a neural network model for solving clique vertex-partition problems in arbitrary non-directed graphs is presented in this paper. A clique of a graph G = (V, E) with a set of vertices V and a set of edges E is a complete subgraph of G where any pair of vertices is connected with an edge. A clique vertex-partition problem of a graph G is to partition every vertex in V into a set of disjointed cliques of G. The clique vertex-partition problem with the minimum number of cliques in an arbitrary graph is known to be NP-complete. The algorithm requires nm processing elements for the n vertex m partition problem. A total of 10 different problems with 8 vertex to 300 vertex graphs were examined where the algorithm found a solution in nearly constant time. The circuit diagram of the neural network model is also proposed in this paper.

Original languageEnglish
Pages (from-to)357-372
Number of pages16
JournalInternational Journal of Electronics
Issue number3
Publication statusPublished - 1992 Mar
Externally publishedYes

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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