Contributions to the future of metaheuristics in the contours of scientific development

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dc.contributor.authorde Souza Sampaio, Nilo Antonio
dc.contributor.authorda Motta Reis, José Salvador [UNESP]
dc.contributor.authorEspuny, Maximilian [UNESP]
dc.contributor.authorCardoso, Ronald Paland
dc.contributor.authorGomes, Fabricio Maciel
dc.contributor.authorPereira, Felix Monteiro
dc.contributor.authorFerreira, Luís César
dc.contributor.authorBarbosa, Motta
dc.contributor.authorSantos, Gilberto
dc.contributor.authorSilva, Messias Borges [UNESP]
dc.contributor.institutionUniversidade do Estado do Rio de Janeiro (UERJ)
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionCentro Federal de Educação Tecnológica Celso Suckow da Fonseca – CEFET-RJ
dc.contributor.institutionPolytechnic Institute of Cavado and Ave – IPCA
dc.date.accessioned2023-03-01T23:40:42Z
dc.date.available2023-03-01T23:40:42Z
dc.date.issued2022-01-01
dc.description.abstractMetaheuristic algorithms solve optimisation problems by identifying the best combination among a set of variables to enhance a function. Within metaheuristics, the main purpose of this work is that of showing the development of research issues about processes related to optimisation and metaheuristics, with a focus on the projection of those issues with greater possibility of development. Optimization processes is one of the most studied fields in artificial intelligence, optimization, logistics, and other applications The main contributions of this work were the identification of the main issues contained in the themes of process optimization and metaheuristics; an analysis of the expansion and retraction of the aforementioned theme; an understanding of convergence and divergence; and an analysis of the stages of development as presented in the gaps of the fifty most commonly mentioned articles. The main finding was to analyze the development of research topics on optimization processes and metaheuristics, focusing on projecting the topics most likely to develop.en
dc.description.affiliationUniversidade do Estado do Rio de Janeiro – UERJ Faculdade de Tecnologia, RJ
dc.description.affiliationUniversidade Estadual Paulista – UNESP Faculdade de Engenharia de Guaratinguetá, Guaratinguetá, SP
dc.description.affiliationUniversidade de São Paulo – USP Escola de Engenharia de Lorena, SP
dc.description.affiliationCentro Federal de Educação Tecnológica Celso Suckow da Fonseca – CEFET-RJ, RJ
dc.description.affiliationPolytechnic Institute of Cavado and Ave – IPCA
dc.description.affiliationUnespUniversidade Estadual Paulista – UNESP Faculdade de Engenharia de Guaratinguetá, Guaratinguetá, SP
dc.identifierhttp://dx.doi.org/10.1590/1806-9649-2022V29E099
dc.identifier.citationGestao e Producao, v. 29.
dc.identifier.doi10.1590/1806-9649-2022V29E099
dc.identifier.issn1806-9649
dc.identifier.issn0104-530X
dc.identifier.scopus2-s2.0-85128508680
dc.identifier.urihttp://hdl.handle.net/11449/241751
dc.language.isoeng
dc.relation.ispartofGestao e Producao
dc.sourceScopus
dc.subjectAlgorithm
dc.subjectMetaheuristics
dc.subjectModelling
dc.subjectOptimization
dc.titleContributions to the future of metaheuristics in the contours of scientific developmenten
dc.titleContribuições para o futuro da metaheurística nos contornos do desenvolvimento científicopt
dc.typeArtigo

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