Volume 21, Number 3 (IJIEPM (New Issue) 2010)                   IJIEPM 2010, 21(3): 45-54 | Back to browse issues page

XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Yaghini M, Lessan J. Solving the Capacitated Clustering Problem Using Simulated Annealing and Genetic Algorithms. IJIEPM. 2010; 21 (3) :45-54
URL: http://ijiepm.iust.ac.ir/article-1-380-en.html

, yaghini@iust.ac.ir
Abstract:   (8995 Views)

  The Capacitated Clustering Problem (CCP) is a classical location problem with various applications in data mining. In the capacitated clustering problem, a set of n entities is to be partitioned into p disjoint clusters, such that the total dissimilarity within each cluster is minimized subject to constraints on maximum cluster capacity. Dissimilarity of a cluster is the sum of the dissimilarities between each entity that belongs to the cluster and the median associated with the cluster. In this paper two solution methods proposed for the problem. First method is a simulation annealing algorithm which uses different neighborhood structures randomly. The second method is a genetic algorithm approach which strengthened by a heuristic local search method. Computational results of test samples from literature demonstrate the robustness and efficiency of the proposed solution methods. This confirms that the proposed algorithm provides high quality solutions in reasonable time .

Full-Text [PDF 500 kb]   (1587 Downloads)    

Add your comments about this article : Your username or email:
Write the security code in the box

Send email to the article author

© 2015 All Rights Reserved | International Journal of Industrial Engineering & Production Management

Designed & Developed by : Yektaweb