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On the exploration and exploitation in popular swarm-based metaheuristic algorithms

It is obvious from wider spectrum of successful applications that metaheuristic algorithms are potential solutions to hard optimization problems. Among such algorithms are swarm-based methods like particle swarm optimization and ant colony optimization which are increasingly attracting new researche...

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Main Authors: Hussain, Kashif, Mohd Salleh, Mohd Najib, Cheng, Shi, Shi, Yuhui
Format: Article
Language:English
Published: Springer 2018
Subjects:
Q Science (General)
Online Access:http://eprints.uthm.edu.my/3465/1/AJ%202018%20%28348%29.pdf
http://eprints.uthm.edu.my/3465/
https://doi.org/10.1007/s00521-018-3592-0
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spelling my.uthm.eprints.34652021-11-17T07:38:34Z http://eprints.uthm.edu.my/3465/ On the exploration and exploitation in popular swarm-based metaheuristic algorithms Hussain, Kashif Mohd Salleh, Mohd Najib Cheng, Shi Shi, Yuhui Q Science (General) It is obvious from wider spectrum of successful applications that metaheuristic algorithms are potential solutions to hard optimization problems. Among such algorithms are swarm-based methods like particle swarm optimization and ant colony optimization which are increasingly attracting new researchers. Despite popularity, the core questions on performance issues are still partially answered due to limited insightful analyses. Mere investigation and comparison of end results may not reveal the reasons behind poor or better performance. This study, therefore, performed in-depth empirical analysis by quantitatively analyzing exploration and exploitation of five swarm-based metaheuristic algorithms. The analysis unearthed explanations the way algorithms performed on numerical problems as well as on real-world application of classification using adaptive neuro-fuzzy inference system (ANFIS) trained by selected metaheuristics. The outcome of empirical study suggested that coherence and consistency in the swarm individuals throughout iterations is the key to success in swarmbased metaheuristic algorithms. The analytical approach adopted in this study may be employed to perform componentwise diversity analysis so that the contribution of each component on performance may be determined for devising efficient search strategies. Springer 2018 Article PeerReviewed text en http://eprints.uthm.edu.my/3465/1/AJ%202018%20%28348%29.pdf Hussain, Kashif and Mohd Salleh, Mohd Najib and Cheng, Shi and Shi, Yuhui (2018) On the exploration and exploitation in popular swarm-based metaheuristic algorithms. Neural Computing and Applications, 13 (3). pp. 7665-7683. ISSN 0941-0643 https://doi.org/10.1007/s00521-018-3592-0
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic Q Science (General)
spellingShingle Q Science (General)
Hussain, Kashif
Mohd Salleh, Mohd Najib
Cheng, Shi
Shi, Yuhui
On the exploration and exploitation in popular swarm-based metaheuristic algorithms
description It is obvious from wider spectrum of successful applications that metaheuristic algorithms are potential solutions to hard optimization problems. Among such algorithms are swarm-based methods like particle swarm optimization and ant colony optimization which are increasingly attracting new researchers. Despite popularity, the core questions on performance issues are still partially answered due to limited insightful analyses. Mere investigation and comparison of end results may not reveal the reasons behind poor or better performance. This study, therefore, performed in-depth empirical analysis by quantitatively analyzing exploration and exploitation of five swarm-based metaheuristic algorithms. The analysis unearthed explanations the way algorithms performed on numerical problems as well as on real-world application of classification using adaptive neuro-fuzzy inference system (ANFIS) trained by selected metaheuristics. The outcome of empirical study suggested that coherence and consistency in the swarm individuals throughout iterations is the key to success in swarmbased metaheuristic algorithms. The analytical approach adopted in this study may be employed to perform componentwise diversity analysis so that the contribution of each component on performance may be determined for devising efficient search strategies.
format Article
author Hussain, Kashif
Mohd Salleh, Mohd Najib
Cheng, Shi
Shi, Yuhui
author_facet Hussain, Kashif
Mohd Salleh, Mohd Najib
Cheng, Shi
Shi, Yuhui
author_sort Hussain, Kashif
title On the exploration and exploitation in popular swarm-based metaheuristic algorithms
title_short On the exploration and exploitation in popular swarm-based metaheuristic algorithms
title_full On the exploration and exploitation in popular swarm-based metaheuristic algorithms
title_fullStr On the exploration and exploitation in popular swarm-based metaheuristic algorithms
title_full_unstemmed On the exploration and exploitation in popular swarm-based metaheuristic algorithms
title_sort on the exploration and exploitation in popular swarm-based metaheuristic algorithms
publisher Springer
publishDate 2018
url http://eprints.uthm.edu.my/3465/1/AJ%202018%20%28348%29.pdf
http://eprints.uthm.edu.my/3465/
https://doi.org/10.1007/s00521-018-3592-0
_version_ 1738581126569525248
score 13.211869

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