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IJMLC 2014 Vol. 4(6): 510-515 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2014.V6.464

Cat Swarm Optimization with a Vibrational Mutation Strategy

Yan Zhang and Yide Ma

Abstract—Cat swarm optimization (CSO), a relatively new swarm intelligence algorithm, exhibits better performance on optimization problems than particle swarm optimization (PSO) and weighted-PSO. This paper presents a variation on the standard CSO algorithm called a vibrational mutation cat swarm optimization, or VMCSO in order to efficiently increase diversity of the swarm in the global searches. Comparing the new algorithm with CSO and several CSO main variants demonstrates the superiority of the VMCSO for the benchmark functions.

Index Terms—Cat Swarm Optimization, Vibrational mutation, Diversity, Swarm intelligence.

Yan Zhang and Yide Ma are with the School of Information Science and Engineering, Lanzhou University, Lanzhou, China (corresponding author : Yide Ma; e-mail: zhangaoliao@ gmail.com, yidema@ gmail.com).


Cite: Yan Zhang and Yide Ma, "Cat Swarm Optimization with a Vibrational Mutation Strategy," International Journal of Machine Learning and Computing vol. 4, no. 6, pp. 510-515, 2014.

General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net

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