Searching Cliques in a Fuzzy Graph Based on an Evolutionary and Biological Method

Authors:
Ikno Kim;Junzo Watada
Affiliations:
Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Japan 808-0135;Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Japan 808-0135
Venue:
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part II
Year:
2009

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Abstract

In this paper, a new and systematic approach for the integration of fuzzy-based methods and biological computation, named as an evolutionary and biological method, is proposed for searching cliques in a fuzzy graph. When dealing with a number of nodes in a graph, the most intractable problem is often detecting the maximum clique, which is automatically obtained from finding a solution to the arranged cliques in descending order. The evolutionary and biological method is proposed to identify all the cliques and to arrange them in a fuzzy graph, and then to structure all the nodes in the graph, based on the searched cliques, in different hierarchical levels. This challenging approach, involving the integration of two techniques, provides a new and better method for solving clique problems.