A Clustering Algorithm using the Tabu Search Approach with Simulated Annealing
S. Chu, J. Roddick, and A. Australia. In Data Mining II-Proceedings of Second International Conference on Data Mining Methods and Databases, page 515--523. (2000)
Abstract
In this paper, an algorithm for cluster generation using tabu search approach with simulated annealing is proposed. The main idea of this algorithm is to use the tabu search approach to generate non-local moves for the clusters and apply the simulated annealing technique to select suitable current best solution so that speed the cluster generation. Experimental results demonstrate the proposed tabu search approach with simulated annealing algorithm for cluster generation is superior to the tabu search approach with Generalised Lloyd algorithm. 1 Clustering Clustering is the process of grouping patterns into a number of clusters, each of which contains the patterns that are similar to each other in some way. The existing clustering algorithms can be simply classied into the following two categories: hierarchical clustering and partitional clustering 1. The hierarchical clustering operates by partitioning the patterns into successively fewer structures. This method gives rise to a d...
Description
A Clustering Algorithm using the Tabu Search Approach with Simulated Annealing
%0 Conference Paper
%1 Chu00aclustering
%A Chu, Shu-Chuan
%A Roddick, John F.
%A Australia, Adelaide
%B In Data Mining II-Proceedings of Second International Conference on Data Mining Methods and Databases
%D 2000
%K 2009 clustering seminar
%P 515--523
%T A Clustering Algorithm using the Tabu Search Approach with Simulated Annealing
%U http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.8618
%X In this paper, an algorithm for cluster generation using tabu search approach with simulated annealing is proposed. The main idea of this algorithm is to use the tabu search approach to generate non-local moves for the clusters and apply the simulated annealing technique to select suitable current best solution so that speed the cluster generation. Experimental results demonstrate the proposed tabu search approach with simulated annealing algorithm for cluster generation is superior to the tabu search approach with Generalised Lloyd algorithm. 1 Clustering Clustering is the process of grouping patterns into a number of clusters, each of which contains the patterns that are similar to each other in some way. The existing clustering algorithms can be simply classied into the following two categories: hierarchical clustering and partitional clustering 1. The hierarchical clustering operates by partitioning the patterns into successively fewer structures. This method gives rise to a d...
@inproceedings{Chu00aclustering,
abstract = {In this paper, an algorithm for cluster generation using tabu search approach with simulated annealing is proposed. The main idea of this algorithm is to use the tabu search approach to generate non-local moves for the clusters and apply the simulated annealing technique to select suitable current best solution so that speed the cluster generation. Experimental results demonstrate the proposed tabu search approach with simulated annealing algorithm for cluster generation is superior to the tabu search approach with Generalised Lloyd algorithm. 1 Clustering Clustering is the process of grouping patterns into a number of clusters, each of which contains the patterns that are similar to each other in some way. The existing clustering algorithms can be simply classied into the following two categories: hierarchical clustering and partitional clustering [1]. The hierarchical clustering operates by partitioning the patterns into successively fewer structures. This method gives rise to a d...},
added-at = {2009-11-12T15:47:33.000+0100},
author = {Chu, Shu-Chuan and Roddick, John F. and Australia, Adelaide},
biburl = {https://www.bibsonomy.org/bibtex/2847138921af99f7c6f55cf68d002b085/k.e.},
booktitle = {In Data Mining II-Proceedings of Second International Conference on Data Mining Methods and Databases},
description = {A Clustering Algorithm using the Tabu Search Approach with Simulated Annealing},
interhash = {4a1119f702f3dc2517a6efc211ea9e18},
intrahash = {847138921af99f7c6f55cf68d002b085},
keywords = {2009 clustering seminar},
pages = {515--523},
timestamp = {2009-11-12T15:47:34.000+0100},
title = {A Clustering Algorithm using the Tabu Search Approach with Simulated Annealing},
url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.8618},
year = 2000
}