Multi-membrane search algorithm.
This research proposes a new multi-membrane search algorithm (MSA) based on cell biological behavior. Cell secretion protein behavior and cell division and fusion strategy are the main inspirations for the algorithm. In order to verify the performance of the algorithm, we used 19 benchmark functions...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2021-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0260512 |
| _version_ | 1819229112679530496 |
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| author | Qi Song Yourui Huang Wenhao Lai Tao Han Shanyong Xu Xue Rong |
| author_facet | Qi Song Yourui Huang Wenhao Lai Tao Han Shanyong Xu Xue Rong |
| author_sort | Qi Song |
| collection | DOAJ |
| description | This research proposes a new multi-membrane search algorithm (MSA) based on cell biological behavior. Cell secretion protein behavior and cell division and fusion strategy are the main inspirations for the algorithm. In order to verify the performance of the algorithm, we used 19 benchmark functions to compare the MSA test results with MVO, GWO, MFO and ALO. The number of iterations of each algorithm on each benchmark function is 100, the population number is 10, and the running is repeated 50 times, and the average and standard deviation of the results are recorded. Tests show that the MSA is competitive in unimodal benchmark functions and multi-modal benchmark functions, and the results in composite benchmark functions are all superior to MVO, MFO, ALO, and GWO algorithms. This paper also uses MSA to solve two classic engineering problems: welded beam design and pressure vessel design. The result of welded beam design is 1.7252, and the result of pressure vessel design is 5887.7052, which is better than other comparison algorithms. Statistical experiments show that MSA is a high-performance algorithm that is competitive in unimodal and multimodal functions, and its performance in compound functions is significantly better than MVO, MFO, ALO, and GWO algorithms. |
| first_indexed | 2024-12-23T11:08:00Z |
| format | Article |
| id | doaj.art-73d796d999c24c64b105e39c741d7ac4 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-23T11:08:00Z |
| publishDate | 2021-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-73d796d999c24c64b105e39c741d7ac42022-12-21T17:49:26ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-011612e026051210.1371/journal.pone.0260512Multi-membrane search algorithm.Qi SongYourui HuangWenhao LaiTao HanShanyong XuXue RongThis research proposes a new multi-membrane search algorithm (MSA) based on cell biological behavior. Cell secretion protein behavior and cell division and fusion strategy are the main inspirations for the algorithm. In order to verify the performance of the algorithm, we used 19 benchmark functions to compare the MSA test results with MVO, GWO, MFO and ALO. The number of iterations of each algorithm on each benchmark function is 100, the population number is 10, and the running is repeated 50 times, and the average and standard deviation of the results are recorded. Tests show that the MSA is competitive in unimodal benchmark functions and multi-modal benchmark functions, and the results in composite benchmark functions are all superior to MVO, MFO, ALO, and GWO algorithms. This paper also uses MSA to solve two classic engineering problems: welded beam design and pressure vessel design. The result of welded beam design is 1.7252, and the result of pressure vessel design is 5887.7052, which is better than other comparison algorithms. Statistical experiments show that MSA is a high-performance algorithm that is competitive in unimodal and multimodal functions, and its performance in compound functions is significantly better than MVO, MFO, ALO, and GWO algorithms.https://doi.org/10.1371/journal.pone.0260512 |
| spellingShingle | Qi Song Yourui Huang Wenhao Lai Tao Han Shanyong Xu Xue Rong Multi-membrane search algorithm. PLoS ONE |
| title | Multi-membrane search algorithm. |
| title_full | Multi-membrane search algorithm. |
| title_fullStr | Multi-membrane search algorithm. |
| title_full_unstemmed | Multi-membrane search algorithm. |
| title_short | Multi-membrane search algorithm. |
| title_sort | multi membrane search algorithm |
| url | https://doi.org/10.1371/journal.pone.0260512 |
| work_keys_str_mv | AT qisong multimembranesearchalgorithm AT youruihuang multimembranesearchalgorithm AT wenhaolai multimembranesearchalgorithm AT taohan multimembranesearchalgorithm AT shanyongxu multimembranesearchalgorithm AT xuerong multimembranesearchalgorithm |