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Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic

In the past few years nature-inspired algorithms are experiencing rapid growth where most optimisation problems in different domains are addressed using it. As a result of this development come the issue of handling a complex optimisation problem within a short period remains very difficult. Symbiot...

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Main Authors: Sa'ad, Suleiman, Abdullah, Muhammed, Abdullah, Azizol, Ayob, Fahrul Hakim
Format: Article
Published: The Association of Professional Researchers and Academicians 2022
Online Access:http://psasir.upm.edu.my/id/eprint/103387/
https://slr-m.com/index.php/home/article/view/29
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id my.upm.eprints.103387
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spelling my.upm.eprints.1033872023-06-08T07:32:03Z http://psasir.upm.edu.my/id/eprint/103387/ Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic Sa'ad, Suleiman Abdullah, Muhammed Abdullah, Azizol Ayob, Fahrul Hakim In the past few years nature-inspired algorithms are experiencing rapid growth where most optimisation problems in different domains are addressed using it. As a result of this development come the issue of handling a complex optimisation problem within a short period remains very difficult. Symbiotic organisms search (SOS) algorithm is one of the nature-inspired metaheuristics that mimics the symbiotic association of organisms in an ecosystem. This paper proposes to investigate symbiotic organisms search algorithms used in handling various optimisation problems in different fields to bring out strengths and weaknesses of the existing algorithms as well as to point out future directions for the upcoming studies in the domain. To achieve that, studies done in optimisation problems using symbiotic organisms search from 2014 – 2020 that are obtained from some databases (Scopus, ScienceDirect, IEEE Xplore, ACM) were surveyed; where the review of various issues related to SOS such as diversity of solution search space, variants, scalability, and applications of the SOS. Finally, future research directions in the area were recommended. The Association of Professional Researchers and Academicians 2022 Article PeerReviewed Sa'ad, Suleiman and Abdullah, Muhammed and Abdullah, Azizol and Ayob, Fahrul Hakim (2022) Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic. The Systematic Literature Review and Meta-Analysis Journal, 3 (1). pp. 1-8. https://slr-m.com/index.php/home/article/view/29 10.54480/slrm.v3i1.29
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description In the past few years nature-inspired algorithms are experiencing rapid growth where most optimisation problems in different domains are addressed using it. As a result of this development come the issue of handling a complex optimisation problem within a short period remains very difficult. Symbiotic organisms search (SOS) algorithm is one of the nature-inspired metaheuristics that mimics the symbiotic association of organisms in an ecosystem. This paper proposes to investigate symbiotic organisms search algorithms used in handling various optimisation problems in different fields to bring out strengths and weaknesses of the existing algorithms as well as to point out future directions for the upcoming studies in the domain. To achieve that, studies done in optimisation problems using symbiotic organisms search from 2014 – 2020 that are obtained from some databases (Scopus, ScienceDirect, IEEE Xplore, ACM) were surveyed; where the review of various issues related to SOS such as diversity of solution search space, variants, scalability, and applications of the SOS. Finally, future research directions in the area were recommended.
format Article
author Sa'ad, Suleiman
Abdullah, Muhammed
Abdullah, Azizol
Ayob, Fahrul Hakim
spellingShingle Sa'ad, Suleiman
Abdullah, Muhammed
Abdullah, Azizol
Ayob, Fahrul Hakim
Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic
author_facet Sa'ad, Suleiman
Abdullah, Muhammed
Abdullah, Azizol
Ayob, Fahrul Hakim
author_sort Sa'ad, Suleiman
title Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic
title_short Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic
title_full Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic
title_fullStr Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic
title_full_unstemmed Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic
title_sort symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic
publisher The Association of Professional Researchers and Academicians
publishDate 2022
url http://psasir.upm.edu.my/id/eprint/103387/
https://slr-m.com/index.php/home/article/view/29
_version_ 1769844457124921344
score 13.211869

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