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Analysis of Vector Evaluated Particle Swarm Optimization Guided by Non-Dominated Solutions : Inertia Weight, Cognitive, and Social Constants

Kian, Sheng Lim and Zuwairie, Ibrahim and Salinda, Buyamin and Anita, Ahmad and Nurul Wahidah, Arshad and Faradila, Naim (2014) Analysis of Vector Evaluated Particle Swarm Optimization Guided by Non-Dominated Solutions : Inertia Weight, Cognitive, and Social Constants. In: 9th International Conference on Innovative Computing, Information and Control, 15-18 June 2014 , Busan, Korea. .

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Abstract

Recently, an improved Vector Evaluated Particle Swarm Optimisation (VEPSO) algorithm is introduced by redefining the swarm's leader as non-dominated solutions. The improved VEPSO algorithm is named as VEPSOnds. Since a parameter tuning of a heuristic algorithm is normally difficult. Hence, 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 to be random value in between 1.5 and 2.5.

Item Type: Conference or Workshop Item (Speeches)
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Ms Suriati Mohd Adam
Date Deposited: 28 Oct 2014 08:07
Last Modified: 08 Feb 2018 02:20
URI: http://umpir.ump.edu.my/id/eprint/6759
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