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Analysis of vector evaluated particle swarm optimization guided by non-dominated solutions: Inertia weight, cognitive, and social constants

Lim, K. S. and Ibrahim, Z. and Buyamin, S. and Ahmad, A. and Shapiai, M. I. and Khalil, K. and Nawawi, S. W. and Arshad, N. W. and Naim, F. (2015) Analysis of vector evaluated particle swarm optimization guided by non-dominated solutions: Inertia weight, cognitive, and social constants. Icic Express Letters, 9 (5). pp. 1279-1284. ISSN 1880-5566

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Official URL: https://www.researchgate.net/publication/281941074...

Abstract

Recently, an improved Vector Evaluated Particle Swarm Optimization (VE PSO) algorithm has been introduced by redefining the swarm’s leader as non-dominated solutions. The improved VEPSO algorithm is named as VEPSO-non-dominated-solution (VEPSOnds). Since a parameter tuning of a heuristic algorithm is normally difficult, in this paper, three important parameters of the improved VEPSO, which are inertia weight, cognitive constant, and social constant, are analyzed. The results suggest that the inertia weight should gradually degrade from 1.0 to 0.4, and both cognitive and social constants are random value in between 1.5 and 2.5. Analysis of vector evaluated particle swarm optimization guided by non-dominated solutions: Inertia weight, cognitive, and social constants.

Item Type:Article
Uncontrolled Keywords:inertia weight, cognitive constant
Subjects:A General Works
Divisions:Electrical Engineering
ID Code:57814
Deposited By: Haliza Zainal
Deposited On:04 Dec 2016 12:07
Last Modified:20 Jun 2017 15:22

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