A TABU SEARCH-BASED ALGORITHM FOR THE FUZZY CLUSTERING PROBLEM

The Fuzzy Clustering Problem (FCP) is a mathematical program which is difficult to solve since it is nonconvex, which implies possession of many local minima. The fuzzy C-means heuristic is the widely known app roach to this problem, but it is guaranteed only to yield local minima . In this paper, we propose a new approach to this problem which is ba sed on tabu search technique, and aims at finding a global solution of FCP. We compare the performance of the algorithm with the fuzzy C-mea ns algorithm. (C) 1997 Pattern Recognition Society. Published by Elsev ier Science Ltd.