Design of hybrids for the minimum sum-of-squares clustering problem

A series of metaheuristic algorithms is proposed and analyzed for the non-hierarchical clustering problem under the criterion of minimum Sum-of-Squares Clustering. These algorithms incorporate genetic operators and Local Search and Tabu Search procedures. The aim is to obtain quality solutions with short computation times. A series of computational experiments has been performed. The proposed algorithms obtain better results than previously reported methods, especially with small numbers of clusters.