Salp Swarm Optimization

Detalhes bibliográficos
Autor(a) principal: Castelli, Mauro
Data de Publicação: 2022
Outros Autores: Manzoni, Luca, Mariot, Luca, Nobile, Marco S., Tangherloni, Andrea
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/126504
Resumo: Castelli, M., Manzoni, L., Mariot, L., Nobile, M. S., & Tangherloni, A. (2022). Salp Swarm Optimization: A critical review. Expert Systems with Applications, 189, 1-12. [116029]. [Advanced online publication on 16 October 2021]. Doi: https://doi.org/10.1016/j.eswa.2021.116029.-----Funding Information: This work was supported by national funds through the FCT (Fundação para a Ciência e a Tecnologia), Portugal by the projects GADgET ( DSAIPA/DS/0022/2018 ) and the financial support from the Slovenian Research Agency, Republic of Slovenia (research core funding no. P5-0410 ).
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spelling Salp Swarm OptimizationA critical reviewMetaheuristicsGlobal optimizationBound constrained optimizationShift invariant functionsEngineering(all)Computer Science ApplicationsArtificial IntelligenceCastelli, M., Manzoni, L., Mariot, L., Nobile, M. S., & Tangherloni, A. (2022). Salp Swarm Optimization: A critical review. Expert Systems with Applications, 189, 1-12. [116029]. [Advanced online publication on 16 October 2021]. Doi: https://doi.org/10.1016/j.eswa.2021.116029.-----Funding Information: This work was supported by national funds through the FCT (Fundação para a Ciência e a Tecnologia), Portugal by the projects GADgET ( DSAIPA/DS/0022/2018 ) and the financial support from the Slovenian Research Agency, Republic of Slovenia (research core funding no. P5-0410 ).In the crowded environment of bio-inspired population-based metaheuristics, the Salp Swarm Optimization (SSO) algorithm recently appeared and immediately gained a lot of momentum. Inspired by the peculiar spatial arrangement of salp colonies, which are displaced in long chains following a leader, this algorithm seems to provide an interesting optimization performance. However, the original work was characterized by some conceptual and mathematical flaws, which influenced all ensuing papers on the subject. In this manuscript, we perform a critical review of SSO, highlighting all the issues present in the literature and their negative effects on the optimization process carried out by this algorithm. We also propose a mathematically correct version of SSO, named Amended Salp Swarm Optimizer (ASSO) that fixes all the discussed problems. We benchmarked the performance of ASSO on a set of tailored experiments, showing that it is able to achieve better results than the original SSO. Finally, we performed an extensive study aimed at understanding whether SSO and its variants provide advantages compared to other metaheuristics. The experimental results, where SSO cannot outperform simple well-known metaheuristics, suggest that the scientific community can safely abandon SSO.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNCastelli, MauroManzoni, LucaMariot, LucaNobile, Marco S.Tangherloni, Andrea2023-10-17T00:33:31Z2022-03-012022-03-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article12application/pdfhttp://hdl.handle.net/10362/126504eng0957-4174PURE: 34401364https://doi.org/10.1016/j.eswa.2021.116029info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-05-22T17:56:47Zoai:run.unl.pt:10362/126504Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-22T17:56:47Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Salp Swarm Optimization
A critical review
title Salp Swarm Optimization
spellingShingle Salp Swarm Optimization
Castelli, Mauro
Metaheuristics
Global optimization
Bound constrained optimization
Shift invariant functions
Engineering(all)
Computer Science Applications
Artificial Intelligence
title_short Salp Swarm Optimization
title_full Salp Swarm Optimization
title_fullStr Salp Swarm Optimization
title_full_unstemmed Salp Swarm Optimization
title_sort Salp Swarm Optimization
author Castelli, Mauro
author_facet Castelli, Mauro
Manzoni, Luca
Mariot, Luca
Nobile, Marco S.
Tangherloni, Andrea
author_role author
author2 Manzoni, Luca
Mariot, Luca
Nobile, Marco S.
Tangherloni, Andrea
author2_role author
author
author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Castelli, Mauro
Manzoni, Luca
Mariot, Luca
Nobile, Marco S.
Tangherloni, Andrea
dc.subject.por.fl_str_mv Metaheuristics
Global optimization
Bound constrained optimization
Shift invariant functions
Engineering(all)
Computer Science Applications
Artificial Intelligence
topic Metaheuristics
Global optimization
Bound constrained optimization
Shift invariant functions
Engineering(all)
Computer Science Applications
Artificial Intelligence
description Castelli, M., Manzoni, L., Mariot, L., Nobile, M. S., & Tangherloni, A. (2022). Salp Swarm Optimization: A critical review. Expert Systems with Applications, 189, 1-12. [116029]. [Advanced online publication on 16 October 2021]. Doi: https://doi.org/10.1016/j.eswa.2021.116029.-----Funding Information: This work was supported by national funds through the FCT (Fundação para a Ciência e a Tecnologia), Portugal by the projects GADgET ( DSAIPA/DS/0022/2018 ) and the financial support from the Slovenian Research Agency, Republic of Slovenia (research core funding no. P5-0410 ).
publishDate 2022
dc.date.none.fl_str_mv 2022-03-01
2022-03-01T00:00:00Z
2023-10-17T00:33:31Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/126504
url http://hdl.handle.net/10362/126504
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0957-4174
PURE: 34401364
https://doi.org/10.1016/j.eswa.2021.116029
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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application/pdf
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instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv mluisa.alvim@gmail.com
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