Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders

Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders

The vector evaluated particle swarm optimisation (VEPSO) algorithm was previously improved by incorporating nondominated solutions for solving multiobjective optimisation problems. However, the obtained solutions did not converge close to the Pareto front and also did not distribute evenly over the...

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Main Authors: Faradila, Naim, Kian, Sheng Lim, Salinda, Buyamin, Anita, Ahmad, Mohd Ibrahim, Shapiai, Marizan, Mubin, Dong, Hwa Kim
Format: Article
Language:English
Published: Hindawi Publishing Corporation 2014
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/9222/
http://umpir.ump.edu.my/id/eprint/9222/
http://umpir.ump.edu.my/id/eprint/9222/
http://umpir.ump.edu.my/id/eprint/9222/1/Improving%20Vector%20Evaluated%20Particle%20Swarm%20Optimisation%20Using%20Multiple%20Nondominated%20Leaders.pdf
id ump-9222
recordtype eprints
spelling ump-92222018-04-26T01:47:10Z http://umpir.ump.edu.my/id/eprint/9222/ Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders Faradila, Naim Kian, Sheng Lim Salinda, Buyamin Anita, Ahmad Mohd Ibrahim, Shapiai Marizan, Mubin Dong, Hwa Kim TK Electrical engineering. Electronics Nuclear engineering The vector evaluated particle swarm optimisation (VEPSO) algorithm was previously improved by incorporating nondominated solutions for solving multiobjective optimisation problems. However, the obtained solutions did not converge close to the Pareto front and also did not distribute evenly over the Pareto front. Therefore, in this study, the concept ofmultiple nondominated leaders is incorporated to further improve the VEPSO algorithm. Hence, multiple nondominated solutions that are best at a respective objective function are used to guide particles in finding optimal solutions. The improved VEPSO is measured by the number of nondominated solutions found, generational distance, spread, and hypervolume.The results from the conducted experiments show that the proposed VEPSO significantly improved the existing VEPSO algorithms. Hindawi Publishing Corporation 2014 Article PeerReviewed application/pdf en cc_by http://umpir.ump.edu.my/id/eprint/9222/1/Improving%20Vector%20Evaluated%20Particle%20Swarm%20Optimisation%20Using%20Multiple%20Nondominated%20Leaders.pdf Faradila, Naim and Kian, Sheng Lim and Salinda, Buyamin and Anita, Ahmad and Mohd Ibrahim, Shapiai and Marizan, Mubin and Dong, Hwa Kim (2014) Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders. The Scientific World Journal, 2014. pp. 1-21. ISSN 2356-6140 (print); 1537-744X (online) http://dx.doi.org/10.1155/2014/364179 doi: 10.1155/2014/364179
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Faradila, Naim
Kian, Sheng Lim
Salinda, Buyamin
Anita, Ahmad
Mohd Ibrahim, Shapiai
Marizan, Mubin
Dong, Hwa Kim
Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders
description The vector evaluated particle swarm optimisation (VEPSO) algorithm was previously improved by incorporating nondominated solutions for solving multiobjective optimisation problems. However, the obtained solutions did not converge close to the Pareto front and also did not distribute evenly over the Pareto front. Therefore, in this study, the concept ofmultiple nondominated leaders is incorporated to further improve the VEPSO algorithm. Hence, multiple nondominated solutions that are best at a respective objective function are used to guide particles in finding optimal solutions. The improved VEPSO is measured by the number of nondominated solutions found, generational distance, spread, and hypervolume.The results from the conducted experiments show that the proposed VEPSO significantly improved the existing VEPSO algorithms.
format Article
author Faradila, Naim
Kian, Sheng Lim
Salinda, Buyamin
Anita, Ahmad
Mohd Ibrahim, Shapiai
Marizan, Mubin
Dong, Hwa Kim
author_facet Faradila, Naim
Kian, Sheng Lim
Salinda, Buyamin
Anita, Ahmad
Mohd Ibrahim, Shapiai
Marizan, Mubin
Dong, Hwa Kim
author_sort Faradila, Naim
title Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders
title_short Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders
title_full Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders
title_fullStr Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders
title_full_unstemmed Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders
title_sort improving vector evaluated particle swarm optimisation using multiple nondominated leaders
publisher Hindawi Publishing Corporation
publishDate 2014
url http://umpir.ump.edu.my/id/eprint/9222/
http://umpir.ump.edu.my/id/eprint/9222/
http://umpir.ump.edu.my/id/eprint/9222/
http://umpir.ump.edu.my/id/eprint/9222/1/Improving%20Vector%20Evaluated%20Particle%20Swarm%20Optimisation%20Using%20Multiple%20Nondominated%20Leaders.pdf
first_indexed 2023-09-18T22:07:34Z
last_indexed 2023-09-18T22:07:34Z
_version_ 1777414810754875392

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