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Tabu-KM: A Hybrid Clustering Algorithm Based on Tabu Search Approach

Credit to Download: 1 | Page Numbers 9 | Abstract Views: 297
Year: 2010
COI code: JR_IJIEPR-21-2_003
Paper Language: English

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Authors Tabu-KM: A Hybrid Clustering Algorithm Based on Tabu Search Approach

  M. Yaghini - Faculty of School of Railway Engineering, Iran University of Science and Technology
  N. Ghazanfari - E-Learning Center-Iran University of Science and Technology


The clustering problem under the criterion of minimum sum of squares is a non-convex and non-linear program, which possesses many locally optimal values, resulting that its solution often falls into these trap and therefore cannot converge to global optima solution. In this paper, an efficient hybrid optimization algorithm is developed for solving this problem, called Tabu-KM. It gathers the optimization property of tabu search and the local search capability of k-means algorithm together. The contribution of proposed algorithm is to produce tabu space for escaping from the trap of local optima and finding better solutionseffectively. The Tabu-KM algorithm is tested on several simulated and standard datasets and its performance is compared with k-means, simulated annealing, tabu search, genetic algorithm, and ant colony optimization algorithms. The experimental results on simulated and standard test problems denote the obustness and efficiency of the algorithm and confirm that the proposed method is a suitable choice for solving data clustering problems.


Clustering problem, Hybrid algorithm, Tabu search algorithm, k-Means algorithm

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COI code: JR_IJIEPR-21-2_003

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Yaghini, M. & N. Ghazanfari, 2010, Tabu-KM: A Hybrid Clustering Algorithm Based on Tabu Search Approach, International Journal of Industrial Engineering & Production Research 21 (2), the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Yaghini, M. & N. Ghazanfari, 2010)
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The University/Research Center Information:
Type: state university
Paper No.: 20366
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