A Tabu Search Based Method for Minimum Sum of Squares Clustering

Abstract

In this article, the metaheuristic algorithm, tabu search, is proposed to deal with the clustering problem under the criterion of minimum sum of squares clustering. The presented method integrates four moving operations and mutation operation into tabu search. Its superiority over local search clustering algorithms and another tabu clustering approach is extensively demonstrated for artificial and real life data sets.