A critical discussion into the core of swarm intelligence algorithms

dc.creatorDávila Patrícia Ferreira Cruz
dc.creatorRenato Dourado Maia
dc.creatorLeandro Nunes de Castro
dc.date.accessioned2022-07-06T14:03:06Z
dc.date.accessioned2025-09-09T00:33:18Z
dc.date.available2022-07-06T14:03:06Z
dc.date.issued2019-03-04
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
dc.description.sponsorshipFAPESP - Fundação de Amparo à Pesquisa do Estado de São Paulo
dc.description.sponsorshipOutra Agência
dc.identifier.doihttps://doi.org/10.1007/s12065-019-00209-
dc.identifier.issn1864-5917
dc.identifier.urihttps://hdl.handle.net/1843/42964
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofEvolutionary Intelligence
dc.rightsAcesso Aberto
dc.subjectAlgoritmos
dc.subjectInteligência coletiva
dc.titleA critical discussion into the core of swarm intelligence algorithms
dc.typeArtigo de periódico
local.citation.epage200
local.citation.spage189
local.citation.volume12
local.description.resumoThe literature is now filled with swarm intelligence algorithms developed by taking inspiration from a number of insects and other animals and phenomena, such as ants, termites, bees, fishes and cockroaches, to name just a few. Many, if not most, of these bioinspirations carry with them some common issues and features which happen at the individual level, promoting very similar collective emergent phenomena. Thus, despite using different biological metaphors as inspiration, most algorithms present a similar structure and it is possible to identify common macro-processes among them. In this context, this paper identifies a set of common features among some well-known swarm-based algorithms and how each of these approaches implement them. By doing this, we provide the community with the core features of swarm-intelligence algorithms. This diagnostic is crucial and timely to the field, because once we are able to list and explain these commonalities, we are also able to better analyze and design swarm intelligence algorithms.
local.publisher.countryBrasil
local.publisher.departmentICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
local.publisher.initialsUFMG
local.url.externahttps://link.springer.com/article/10.1007/s12065-019-00209-6

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