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 a small number of clusters.

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