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.
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Liu, Y., Wang, L., Chen, K. (2005). A Tabu Search Based Method for Minimum Sum of Squares Clustering. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds) Pattern Recognition and Data Mining. ICAPR 2005. Lecture Notes in Computer Science, vol 3686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11551188_27
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DOI: https://doi.org/10.1007/11551188_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28757-5
Online ISBN: 978-3-540-28758-2
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