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

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 t...

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Main Authors: Kian, Sheng Lim, Zuwairie, Ibrahim, Salinda, Buyamin, Anita, Ahmad, Nurul Wahidah, Arshad, Faradila, Naim
Format: Conference or Workshop Item
Language:English
Published: 2014
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/6759/
http://umpir.ump.edu.my/id/eprint/6759/1/Analysis_of_Vector_Evaluated_Particle_Swarm_Optimization_Guided_by_Non-.PDF
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author Kian, Sheng Lim
Zuwairie, Ibrahim
Salinda, Buyamin
Anita, Ahmad
Nurul Wahidah, Arshad
Faradila, Naim
author_facet Kian, Sheng Lim
Zuwairie, Ibrahim
Salinda, Buyamin
Anita, Ahmad
Nurul Wahidah, Arshad
Faradila, Naim
author_sort Kian, Sheng Lim
building UMP Institutional Repository
collection Online Access
description 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.
first_indexed 2025-11-15T01:28:17Z
format Conference or Workshop Item
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institution Universiti Malaysia Pahang
institution_category Local University
language English
last_indexed 2025-11-15T01:28:17Z
publishDate 2014
recordtype eprints
repository_type Digital Repository
spelling ump-67592018-02-08T02:20:38Z http://umpir.ump.edu.my/id/eprint/6759/ Analysis of Vector Evaluated Particle Swarm Optimization Guided by Non-Dominated Solutions : Inertia Weight, Cognitive, and Social Constants Kian, Sheng Lim Zuwairie, Ibrahim Salinda, Buyamin Anita, Ahmad Nurul Wahidah, Arshad Faradila, Naim TK Electrical engineering. Electronics Nuclear engineering 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. 2014 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/6759/1/Analysis_of_Vector_Evaluated_Particle_Swarm_Optimization_Guided_by_Non-.PDF 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. . (Published)
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Kian, Sheng Lim
Zuwairie, Ibrahim
Salinda, Buyamin
Anita, Ahmad
Nurul Wahidah, Arshad
Faradila, Naim
Analysis of Vector Evaluated Particle Swarm Optimization Guided by Non-Dominated Solutions : Inertia Weight, Cognitive, and Social Constants
title Analysis of Vector Evaluated Particle Swarm Optimization Guided by Non-Dominated Solutions : Inertia Weight, Cognitive, and Social Constants
title_full Analysis of Vector Evaluated Particle Swarm Optimization Guided by Non-Dominated Solutions : Inertia Weight, Cognitive, and Social Constants
title_fullStr Analysis of Vector Evaluated Particle Swarm Optimization Guided by Non-Dominated Solutions : Inertia Weight, Cognitive, and Social Constants
title_full_unstemmed Analysis of Vector Evaluated Particle Swarm Optimization Guided by Non-Dominated Solutions : Inertia Weight, Cognitive, and Social Constants
title_short Analysis of Vector Evaluated Particle Swarm Optimization Guided by Non-Dominated Solutions : Inertia Weight, Cognitive, and Social Constants
title_sort analysis of vector evaluated particle swarm optimization guided by non-dominated solutions : inertia weight, cognitive, and social constants
topic TK Electrical engineering. Electronics Nuclear engineering
url http://umpir.ump.edu.my/id/eprint/6759/
http://umpir.ump.edu.my/id/eprint/6759/1/Analysis_of_Vector_Evaluated_Particle_Swarm_Optimization_Guided_by_Non-.PDF