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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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020
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| Subjects: | |
| Online Access: | 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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| Institution: | Universiti Malaysia Pahang |
| Language: | English |
| Summary: | 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. |
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