A New Swarm Intelligence Approach for Clustering Based on Krill Herd with Elitism Strategy

As one of the most popular and well-recognized clustering methods, fuzzy C-means (FCM) clustering algorithm is the basis of other fuzzy clustering analysis methods in theory and application respects. However, FCM algorithm is essentially a local search optimization algorithm. Therefore, sometimes, i...

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Bibliographic Details
Published in:Algorithms 2015-12, Vol.8 (4), p.951-964
Main Authors: Li, Zhi-Yong, Yi, Jiao-Hong, Wang, Gai-Ge
Format: Article
Language:English
Subjects:
clustering
elitism strategy
krill herd
swarm intelligence
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Summary:As one of the most popular and well-recognized clustering methods, fuzzy C-means (FCM) clustering algorithm is the basis of other fuzzy clustering analysis methods in theory and application respects. However, FCM algorithm is essentially a local search optimization algorithm. Therefore, sometimes, it may fail to find the global optimum. For the purpose of getting over the disadvantages of FCM algorithm, a new version of the krill herd (KH) algorithm with elitism strategy, called KHE, is proposed to solve the clustering problem. Elitism tragedy has a strong ability of preventing the krill population from degrading. In addition, the well-selected parameters are used in the KHE method instead of originating from nature. Through an array of simulation experiments, the results show that the KHE is indeed a good choice for solving general benchmark problems and fuzzy clustering analyses.
ISSN:1999-4893
1999-4893
DOI:10.3390/a8040951