Title :
Fuzzy tabu search method for the clustering problem
Author :
Xu, Hong-Bing ; Wang, Hou-jun ; Li, Chun-Guang
Author_Institution :
Coll. of Autom. Control, Univ. of Electron. Sci. & Technol. of China, Sichuan, China
Abstract :
In this paper, the clustering problem (CP) of clustering m objects into c clusters is considered. The objects are represented by points in n-dimensional Euclidean space, and the objective is to classify these m points into c groups so that the distance between points within a cluster and its center is minimized. The problem is an optimization problem that has many local minima. In this paper, we develop a novel fuzzy tabu search (FTS) method for solving this problem. Benefits of the proposed algorithm are illustrated by the numerical results. The obtained results are compared with the standard tabu search method.
Keywords :
fuzzy set theory; minimisation; pattern clustering; search problems; CP; FTS method; clustering problem; fuzzy tabu search method; local minima; minimization; multidimensional Euclidean space; optimization; Automatic control; Clustering algorithms; Educational institutions; Euclidean distance; Fuzzy logic; Geoscience; Information analysis; Pattern analysis; Search methods; Space technology;
Conference_Titel :
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7508-4
DOI :
10.1109/ICMLC.2002.1174508