An Adaptive Fuzzy Symbiotic Organisms Search Algorithm and Its Applications
This paper discusses the development of a Symbiotic Organisms Search Algorithm (SOS) variant, called Adaptive Fuzzy SOS (FSOS). Like SOS, FSOS exploits three types of symbiosis operators namely mutualism, commensalism, and parasitism in order to undertake the search process. Unlike SOS, FSOS is able...
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my.ump.umpir.336592022-04-11T02:32:01Z http://umpir.ump.edu.my/id/eprint/33659/ An Adaptive Fuzzy Symbiotic Organisms Search Algorithm and Its Applications Nurul Asyikin, Zainal Azad, Saiful Kamal Z., Zamli QA Mathematics This paper discusses the development of a Symbiotic Organisms Search Algorithm (SOS) variant, called Adaptive Fuzzy SOS (FSOS). Like SOS, FSOS exploits three types of symbiosis operators namely mutualism, commensalism, and parasitism in order to undertake the search process. Unlike SOS, FSOS is able to adaptively select a single or any combination of mutualism, commensalism, and parasitism update operator(s) as the search progresses based on the current search status controlled by their individual probabilities via the fuzzy decision-making. To validate its performance, we have evaluated FSOS to solve 23 benchmark functions and take a t-way test generation as our case study. Experimental results demonstrate that FSOS exhibits competitive performance against its predecessor (SOS) and other competing metaheuristic algorithms. IEEE 2020 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/33659/1/An%20Adaptive%20Fuzzy%20Symbiotic%20Organisms%20Search%20Algorithm%20and%20Its%20Applications%20%281%29.pdf Nurul Asyikin, Zainal and Azad, Saiful and Kamal Z., Zamli (2020) An Adaptive Fuzzy Symbiotic Organisms Search Algorithm and Its Applications. IEEE Access, 8. pp. 225384-225406. ISSN 2169-3536 https://doi.org/10.1109/ACCESS.2020.3042196 https://doi.org/10.1109/ACCESS.2020.3042196 |
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QA Mathematics Nurul Asyikin, Zainal Azad, Saiful Kamal Z., Zamli An Adaptive Fuzzy Symbiotic Organisms Search Algorithm and Its Applications |
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This paper discusses the development of a Symbiotic Organisms Search Algorithm (SOS) variant, called Adaptive Fuzzy SOS (FSOS). Like SOS, FSOS exploits three types of symbiosis operators namely mutualism, commensalism, and parasitism in order to undertake the search process. Unlike SOS, FSOS is able to adaptively select a single or any combination of mutualism, commensalism, and parasitism update operator(s) as the search progresses based on the current search status controlled by their individual probabilities via the fuzzy decision-making. To validate its performance, we have evaluated FSOS to solve 23 benchmark functions and take a t-way test generation as our case study. Experimental results demonstrate that FSOS exhibits competitive performance against its predecessor (SOS) and other competing metaheuristic algorithms. |
format |
Article |
author |
Nurul Asyikin, Zainal Azad, Saiful Kamal Z., Zamli |
author_facet |
Nurul Asyikin, Zainal Azad, Saiful Kamal Z., Zamli |
author_sort |
Nurul Asyikin, Zainal |
title |
An Adaptive Fuzzy Symbiotic Organisms Search Algorithm and Its Applications |
title_short |
An Adaptive Fuzzy Symbiotic Organisms Search Algorithm and Its Applications |
title_full |
An Adaptive Fuzzy Symbiotic Organisms Search Algorithm and Its Applications |
title_fullStr |
An Adaptive Fuzzy Symbiotic Organisms Search Algorithm and Its Applications |
title_full_unstemmed |
An Adaptive Fuzzy Symbiotic Organisms Search Algorithm and Its Applications |
title_sort |
adaptive fuzzy symbiotic organisms search algorithm and its applications |
publisher |
IEEE |
publishDate |
2020 |
url |
http://umpir.ump.edu.my/id/eprint/33659/1/An%20Adaptive%20Fuzzy%20Symbiotic%20Organisms%20Search%20Algorithm%20and%20Its%20Applications%20%281%29.pdf http://umpir.ump.edu.my/id/eprint/33659/ https://doi.org/10.1109/ACCESS.2020.3042196 https://doi.org/10.1109/ACCESS.2020.3042196 |
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13.209306 |