A tabu search approach for the minimum sum-of-squares clustering problem

Authors:
Yongguo Liu;Zhang Yi;Hong Wu;Mao Ye;Kefei Chen
Affiliations:
School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, PR China and State Key Laboratory for Novel Software Technology, Nanjing Unive ...;School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, PR China;School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, PR China;School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, PR China;Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai 200030, PR China
Venue:
Information Sciences: an International Journal
Year:
2008

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Abstract

In this paper, a tabu search based clustering approach called TS-Clustering is proposed to deal with the minimum sum-of-squares clustering problem. In the TS-Clustering algorithm, five improvement operations and three neighborhood modes are given. The improvement operation is used to enhance the clustering solution obtained in the process of iterations, and the neighborhood mode is used to create the neighborhood of tabu search. The superiority of the proposed method over some known clustering techniques is demonstrated for artificial and real life data sets.