INFORMATION CHANGE THE WORLD

International Journal of Information Technology and Computer Science(IJITCS)

ISSN: 2074-9007 (Print), ISSN: 2074-9015 (Online)

Published By: MECS Press

IJITCS Vol.5, No.11, Oct. 2013

A Novel Cat Swarm Optimization Algorithm for Unconstrained Optimization Problems

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Author(s)

Meysam Orouskhani, Yasin Orouskhani, Mohammad Mansouri, Mohammad Teshnehlab

Index Terms

Swarm Intelligence, Cat Swarm Optimization, Evolutionary Algorithms

Abstract

Cat Swarm Optimization (CSO) is one of the new swarm intelligence algorithms for finding the best global solution. Because of complexity, sometimes the pure CSO takes a long time to converge and cannot achieve the accurate solution. For solving this problem and improving the convergence accuracy level, we propose a new improved CSO namely ‘Adaptive Dynamic Cat Swarm Optimization’. First, we add a new adaptive inertia weight to velocity equation and then use an adaptive acceleration coefficient. Second, by using the information of two previous/next dimensions and applying a new factor, we reach to a new position update equation composing the average of position and velocity information. Experimental results for six test functions show that in comparison with the pure CSO, the proposed CSO can takes a less time to converge and can find the best solution in less iteration.

Cite This Paper

Meysam Orouskhani, Yasin Orouskhani, Mohammad Mansouri, Mohammad Teshnehlab,"A Novel Cat Swarm Optimization Algorithm for Unconstrained Optimization Problems", International Journal of Information Technology and Computer Science(IJITCS), vol.5, no.11, pp.32-41, 2013. DOI: 10.5815/ijitcs.2013.11.04

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