Massive Conscious Neighborhood-Based Crow Search Algorithm for the Pseudo-Coloring Problem

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Autor(es): dc.contributorUniversidade Federal de São Carlos (UFSCar)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorWeierstrass Institute-
Autor(es): dc.contributorIslamic Azad University-
Autor(es): dc.creatorSimplicio Viana, Monique-
Autor(es): dc.creatorContreras, Rodrigo Colnago-
Autor(es): dc.creatorPessoa, Paulo Cavalcanti-
Autor(es): dc.creatorBongarti, Marcelo Adriano dos Santos-
Autor(es): dc.creatorZamani, Hoda-
Autor(es): dc.creatorGuido, Rodrigo Capobianco-
Autor(es): dc.creatorMorandinJunior, Orides-
Data de aceite: dc.date.accessioned2025-08-21T20:41:25Z-
Data de disponibilização: dc.date.available2025-08-21T20:41:25Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2023-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/978-981-97-7181-3_15-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/297165-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/297165-
Descrição: dc.descriptionThe pseudo-coloring problem (PsCP) is a combinatorial optimization challenge that involves assigning colors to elements in a way that meets specific criteria, often related to minimizing conflicts or maximizing some form of utility. A variety of metaheuristic algorithms have been developed to solve PsCP efficiently. However, these algorithms sometimes struggle with the quality of solutions, impacting their ability to achieve optimal or near-optimal results reliably. To overcome these issues, this study introduces an adapted conscious neighborhood-based crow search algorithm (CCSA) and a massive variant of CCSA specifically tailored for PsCP. The performance of CCSA and MCCSA are evaluated on real and synthetic images and compared with state-of-the-art optimizers. The results showed that the adapted CCSA and MCCSA outperformed offering an effective strategy for image pseudo-colorization.-
Descrição: dc.descriptionFederal University of São Carlos, SP-
Descrição: dc.descriptionInstitute of Biosciences Letters and Exact Sciences São Paulo State University (UNESP), SP-
Descrição: dc.descriptionUniversity of São Paulo, SP-
Descrição: dc.descriptionWeierstrass Institute-
Descrição: dc.descriptionFaculty of Computer Engineering Islamic Azad University-
Descrição: dc.descriptionBig Data Research Center Najafabad Branch Islamic Azad University-
Descrição: dc.descriptionInstitute of Biosciences Letters and Exact Sciences São Paulo State University (UNESP), SP-
Formato: dc.format182-196-
Idioma: dc.languageen-
Relação: dc.relationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectColor Spaces-
Palavras-chave: dc.subjectCrow Search Algorithm-
Palavras-chave: dc.subjectMassive Local Search-
Palavras-chave: dc.subjectOptimization-
Palavras-chave: dc.subjectPseudo-Coloring Problem-
Título: dc.titleMassive Conscious Neighborhood-Based Crow Search Algorithm for the Pseudo-Coloring Problem-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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