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Impact of initialization of a modified particle swarm optimization on cooperative source searching

Swarm robotic is well known for its flexibility, scalability and robustness that make it suitable for solving many real-world problems. Source searching which is characterized by complex operation due to the spatial characteristic of the source intensity distribution, uncertain searching environment...

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Main Authors: Ab. Majid, Mad Helmi, Arshad, Mohd Rizal, Yahya, Mohd Faid, Ibrahim, Abu Bakar
Format: Article
Language:English
Published: Institute of Advanced Engineering and Science 2023
Online Access:http://eprints.utem.edu.my/id/eprint/27264/2/0262901012024662.PDF
http://eprints.utem.edu.my/id/eprint/27264/
https://ijece.iaescore.com/index.php/IJECE/article/view/32973/17074
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spelling my.utem.eprints.272642024-07-01T14:30:51Z http://eprints.utem.edu.my/id/eprint/27264/ Impact of initialization of a modified particle swarm optimization on cooperative source searching Ab. Majid, Mad Helmi Arshad, Mohd Rizal Yahya, Mohd Faid Ibrahim, Abu Bakar Swarm robotic is well known for its flexibility, scalability and robustness that make it suitable for solving many real-world problems. Source searching which is characterized by complex operation due to the spatial characteristic of the source intensity distribution, uncertain searching environments and rigid searching constraints is an example of application where swarm robotics can be applied. Particle swarm optimization (PSO) is one of the famous algorithms have been used for source searching where its effectiveness depends on several factors. Improper parameter selection may lead to a premature convergence and thus robots will fail (i.e., low success rate) to locate the source within the given searching constraints. Additionally, target overshooting and improper initialization strategies may lead to a nonoptimal (i.e., take longer time to converge) target searching. In this study, a modified PSO and three different initializations strategies (i.e., random, equidistant and centralized) were proposed. The findings shown that the proposed PSO model successfully reduce the target overshooting by choosing optimal PSO parameters and has better convergence rate and success rate compared to the benchmark algorithms. Additionally, the findings also indicate that the random initialization give better searching success compared to equidistant and centralize initialization. Institute of Advanced Engineering and Science 2023 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/27264/2/0262901012024662.PDF Ab. Majid, Mad Helmi and Arshad, Mohd Rizal and Yahya, Mohd Faid and Ibrahim, Abu Bakar (2023) Impact of initialization of a modified particle swarm optimization on cooperative source searching. International Journal of Electrical and Computer Engineering, 14 (1). pp. 218-229. ISSN 2088-8708 https://ijece.iaescore.com/index.php/IJECE/article/view/32973/17074 10.11591/ijece.v14i1.pp218-229
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description Swarm robotic is well known for its flexibility, scalability and robustness that make it suitable for solving many real-world problems. Source searching which is characterized by complex operation due to the spatial characteristic of the source intensity distribution, uncertain searching environments and rigid searching constraints is an example of application where swarm robotics can be applied. Particle swarm optimization (PSO) is one of the famous algorithms have been used for source searching where its effectiveness depends on several factors. Improper parameter selection may lead to a premature convergence and thus robots will fail (i.e., low success rate) to locate the source within the given searching constraints. Additionally, target overshooting and improper initialization strategies may lead to a nonoptimal (i.e., take longer time to converge) target searching. In this study, a modified PSO and three different initializations strategies (i.e., random, equidistant and centralized) were proposed. The findings shown that the proposed PSO model successfully reduce the target overshooting by choosing optimal PSO parameters and has better convergence rate and success rate compared to the benchmark algorithms. Additionally, the findings also indicate that the random initialization give better searching success compared to equidistant and centralize initialization.
format Article
author Ab. Majid, Mad Helmi
Arshad, Mohd Rizal
Yahya, Mohd Faid
Ibrahim, Abu Bakar
spellingShingle Ab. Majid, Mad Helmi
Arshad, Mohd Rizal
Yahya, Mohd Faid
Ibrahim, Abu Bakar
Impact of initialization of a modified particle swarm optimization on cooperative source searching
author_facet Ab. Majid, Mad Helmi
Arshad, Mohd Rizal
Yahya, Mohd Faid
Ibrahim, Abu Bakar
author_sort Ab. Majid, Mad Helmi
title Impact of initialization of a modified particle swarm optimization on cooperative source searching
title_short Impact of initialization of a modified particle swarm optimization on cooperative source searching
title_full Impact of initialization of a modified particle swarm optimization on cooperative source searching
title_fullStr Impact of initialization of a modified particle swarm optimization on cooperative source searching
title_full_unstemmed Impact of initialization of a modified particle swarm optimization on cooperative source searching
title_sort impact of initialization of a modified particle swarm optimization on cooperative source searching
publisher Institute of Advanced Engineering and Science
publishDate 2023
url http://eprints.utem.edu.my/id/eprint/27264/2/0262901012024662.PDF
http://eprints.utem.edu.my/id/eprint/27264/
https://ijece.iaescore.com/index.php/IJECE/article/view/32973/17074
_version_ 1804070306921316352
score 13.211869

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