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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...

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Detalles Bibliográficos
Autores principales: Song, Qi, Huang, Yourui, Lai, Wenhao, Han, Tao, XU, Shanyong, Rong, Xue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8648127/
https://www.ncbi.nlm.nih.gov/pubmed/34871309
http://dx.doi.org/10.1371/journal.pone.0260512
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author Song, Qi
Huang, Yourui
Lai, Wenhao
Han, Tao
XU, Shanyong
Rong, Xue
author_facet Song, Qi
Huang, Yourui
Lai, Wenhao
Han, Tao
XU, Shanyong
Rong, Xue
author_sort Song, Qi
collection PubMed
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.
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spelling pubmed-86481272021-12-07 Multi-membrane search algorithm Song, Qi Huang, Yourui Lai, Wenhao Han, Tao XU, Shanyong Rong, Xue PLoS One Research Article 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. Public Library of Science 2021-12-06 /pmc/articles/PMC8648127/ /pubmed/34871309 http://dx.doi.org/10.1371/journal.pone.0260512 Text en © 2021 Song et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Song, Qi
Huang, Yourui
Lai, Wenhao
Han, Tao
XU, Shanyong
Rong, Xue
Multi-membrane search algorithm
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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8648127/
https://www.ncbi.nlm.nih.gov/pubmed/34871309
http://dx.doi.org/10.1371/journal.pone.0260512
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