A tabu search approach to the fuzzy clustering problem

In this paper we consider the fuzzy clustering problem. This is a nonconvex problem that has many local minima. It has been studied by many researchers and the most well-known method is the fuzzy c-means algorithm. We develop a new algorithm for solving this problem based on a tabu search technique. Preliminary computational experience on the developed algorithm are encouraging and compare favorably with results from other methods.