An Improved Whale Optimization Algorithm Based on Different Searching Paths and Perceptual Disturbance
Whale optimization algorithm (WOA) is a swarm intelligence optimization algorithm inspired by humpback whale hunting behavior. WOA has many similarities with other swarm intelligence algorithms (PSO, GWO, etc.). WOA’s unique search mechanism enables it to have a strong global search capability while...
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ftdoajarticles:oai:doaj.org/article:87419b9242044be79f3543890ef15c41 2023-05-15T16:36:06+02:00 An Improved Whale Optimization Algorithm Based on Different Searching Paths and Perceptual Disturbance Wei-zhen Sun Jie-sheng Wang Xian Wei 2018-06-01T00:00:00Z https://doi.org/10.3390/sym10060210 https://doaj.org/article/87419b9242044be79f3543890ef15c41 EN eng MDPI AG http://www.mdpi.com/2073-8994/10/6/210 https://doaj.org/toc/2073-8994 2073-8994 doi:10.3390/sym10060210 https://doaj.org/article/87419b9242044be79f3543890ef15c41 Symmetry, Vol 10, Iss 6, p 210 (2018) whale optimization algorithm searching path function optimization Mathematics QA1-939 article 2018 ftdoajarticles https://doi.org/10.3390/sym10060210 2022-12-30T20:40:20Z Whale optimization algorithm (WOA) is a swarm intelligence optimization algorithm inspired by humpback whale hunting behavior. WOA has many similarities with other swarm intelligence algorithms (PSO, GWO, etc.). WOA’s unique search mechanism enables it to have a strong global search capability while taking into account the strong global search capabilities. In this work, considering the the deficiency of WOA in local search mechanism, combined with the optimization methods of other group intelligent algorithms, perceptual perturbation mechanism is introduced, which makes the agent perform more detailed searches near the local extreme point. At the same time, since the WOA uses a logarithmic spiral curve, the agent cannot fully search all the spaces within its search range, even though the introduction of the perturbation mechanism may still lead to the algorithm falling into a local optimum. Therefore, the equal pitch Archimedes spiral curve is chosen to replace the classic logarithmic spiral curve. In order to fully verify the effect of the search path on the performance of the algorithm, several other spiral curves have been chosen for experimental comparison. By utilizing the 23 benchmark test functions, the simulation results show that WOA (PDWOA) with perceptual perturbation significantly outperforms the standard WOA. Then, based on the PDWOA, the effect of the search path on the performance of the algorithm has been verified. The simulation results show that the equal pitch of the Archimedean spiral curve is best. Article in Journal/Newspaper Humpback Whale Directory of Open Access Journals: DOAJ Articles Symmetry 10 6 210 |
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Directory of Open Access Journals: DOAJ Articles |
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whale optimization algorithm searching path function optimization Mathematics QA1-939 |
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whale optimization algorithm searching path function optimization Mathematics QA1-939 Wei-zhen Sun Jie-sheng Wang Xian Wei An Improved Whale Optimization Algorithm Based on Different Searching Paths and Perceptual Disturbance |
topic_facet |
whale optimization algorithm searching path function optimization Mathematics QA1-939 |
description |
Whale optimization algorithm (WOA) is a swarm intelligence optimization algorithm inspired by humpback whale hunting behavior. WOA has many similarities with other swarm intelligence algorithms (PSO, GWO, etc.). WOA’s unique search mechanism enables it to have a strong global search capability while taking into account the strong global search capabilities. In this work, considering the the deficiency of WOA in local search mechanism, combined with the optimization methods of other group intelligent algorithms, perceptual perturbation mechanism is introduced, which makes the agent perform more detailed searches near the local extreme point. At the same time, since the WOA uses a logarithmic spiral curve, the agent cannot fully search all the spaces within its search range, even though the introduction of the perturbation mechanism may still lead to the algorithm falling into a local optimum. Therefore, the equal pitch Archimedes spiral curve is chosen to replace the classic logarithmic spiral curve. In order to fully verify the effect of the search path on the performance of the algorithm, several other spiral curves have been chosen for experimental comparison. By utilizing the 23 benchmark test functions, the simulation results show that WOA (PDWOA) with perceptual perturbation significantly outperforms the standard WOA. Then, based on the PDWOA, the effect of the search path on the performance of the algorithm has been verified. The simulation results show that the equal pitch of the Archimedean spiral curve is best. |
format |
Article in Journal/Newspaper |
author |
Wei-zhen Sun Jie-sheng Wang Xian Wei |
author_facet |
Wei-zhen Sun Jie-sheng Wang Xian Wei |
author_sort |
Wei-zhen Sun |
title |
An Improved Whale Optimization Algorithm Based on Different Searching Paths and Perceptual Disturbance |
title_short |
An Improved Whale Optimization Algorithm Based on Different Searching Paths and Perceptual Disturbance |
title_full |
An Improved Whale Optimization Algorithm Based on Different Searching Paths and Perceptual Disturbance |
title_fullStr |
An Improved Whale Optimization Algorithm Based on Different Searching Paths and Perceptual Disturbance |
title_full_unstemmed |
An Improved Whale Optimization Algorithm Based on Different Searching Paths and Perceptual Disturbance |
title_sort |
improved whale optimization algorithm based on different searching paths and perceptual disturbance |
publisher |
MDPI AG |
publishDate |
2018 |
url |
https://doi.org/10.3390/sym10060210 https://doaj.org/article/87419b9242044be79f3543890ef15c41 |
genre |
Humpback Whale |
genre_facet |
Humpback Whale |
op_source |
Symmetry, Vol 10, Iss 6, p 210 (2018) |
op_relation |
http://www.mdpi.com/2073-8994/10/6/210 https://doaj.org/toc/2073-8994 2073-8994 doi:10.3390/sym10060210 https://doaj.org/article/87419b9242044be79f3543890ef15c41 |
op_doi |
https://doi.org/10.3390/sym10060210 |
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Symmetry |
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210 |
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1766026405117689856 |