N Razizadeh - Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran
M. A. Badamchizaeh
M. S.G. Ghasempour - Industrial Engineering Department, Amirkabir University of Technology, Tehran, Iran

In this paper a new hybrid clustering method is presented which uses fuzzy logic and genetic algorithm. There are two main phases that should beinvestigated. The first is coding hybrid clustering problem in a way that could be solved by genetic algorithm. The other is designing an evaluation functionwhich conducts the potential results to the global optimum. In this paper, a novel fuzzy criterion for evaluating the final partition is proposed which usesstring representation of ensemble of primary clusters. The objective function tries to maximize the agreement between the ensemble members as well as minimize thedisagreement simultaneously. The efficiency of the proposed method is evaluated by multiple standarddatabases. The promising obtained results show theoutperforming of the proposed method compared to the other well known clustering method

Hybrid Clustering, Fuzzy Logic, Genetic Algorithm