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

2008 ◽  
Vol 178 (12) ◽  
pp. 2680-2704 ◽  
Author(s):  
Yongguo Liu ◽  
Zhang Yi ◽  
Hong Wu ◽  
Mao Ye ◽  
Kefei Chen
Keyword(s):  
Tabu Search ◽  
Sum Of Squares ◽  
Clustering Problem ◽  
Search Approach

A Tabu search approach to the clustering problem

1995 ◽  
Vol 28 (9) ◽  
pp. 1443-1451 ◽  
Author(s):  
Khaled S. Al-Sultan
Keyword(s):  
Tabu Search ◽  
Clustering Problem ◽  
Search Approach

A Modified Tabu Search Approach for the Clustering Problem

2011 ◽  
Vol 11 (19) ◽  
pp. 3447-3453 ◽  
Author(s):  
Adnan Kharroushe ◽  
Salwani Abdullah ◽  
Mohd Zakree Ahmad Nazr
Keyword(s):  
Tabu Search ◽  
Clustering Problem ◽  
Search Approach

CLUSTERING USING AN IMPROVED HYBRID GENETIC ALGORITHM

2007 ◽  
Vol 16 (06) ◽  
pp. 919-934
Author(s):  
YONGGUO LIU ◽  
XIAORONG PU ◽  
YIDONG SHEN ◽  
ZHANG YI ◽  
XIAOFENG LIAO
Keyword(s):  
Genetic Algorithm ◽  
Clustering Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Sum Of Squares ◽  
Clustering Methods ◽  
Clustering Problem ◽  
Mutation Operation ◽  
Iteration Methods ◽  
Genetic Clustering ◽  
The Individual

In this article, a new genetic clustering algorithm called the Improved Hybrid Genetic Clustering Algorithm (IHGCA) is proposed to deal with the clustering problem under the criterion of minimum sum of squares clustering. In IHGCA, the improvement operation including five local iteration methods is developed to tune the individual and accelerate the convergence speed of the clustering algorithm, and the partition-absorption mutation operation is designed to reassign objects among different clusters. By experimental simulations, its superiority over some known genetic clustering methods is demonstrated.

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