Evaluating Genetic Algorithms with Different Population Structures on a Lot Sizing and Scheduling Problem

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Federal de Lavras (UFLA)-
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.creatorMotta Toledo, Claudio Fabiano-
Autor(es): dc.creatorFranga, Paulo Morelato [UNESP]-
Autor(es): dc.creatorRosa, Kalianne Almeida-
Autor(es): dc.creatorACM-
Data de aceite: dc.date.accessioned2022-02-22T00:07:31Z-
Data de disponibilização: dc.date.available2022-02-22T00:07:31Z-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2008-01-01-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/195936-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/195936-
Descrição: dc.descriptionThis paper studies the use of different population structures in a Genetic Algorithm (GA) applied to lot sizing and scheduling problems. The population approaches are divided into two types: single-population and multi-population. The first type has a non-structured single population. The multi-population type presents non-structured and structured populations organized in binary and ternary trees. Each population approach is tested on lot sizing and scheduling problems found in soft drink companies. These problems have two interdependent levels with decisions concerning raw material storage and soft drink bottling. The challenge is to simultaneously determine the lot sizing and scheduling of raw materials in tanks and products in lines. Computational results are reported allowing determining the better population structure for the set of problem instances evaluated.-
Descrição: dc.descriptionUniv Fed Lavras, Dept Ciencia Comp, BR-37200000 Lavras, MG, Brazil-
Descrição: dc.descriptionUniv Estadual Paulista, Dept Mat Estat & Comp, BR-19060900 P Prudente, SP, Brazil-
Descrição: dc.descriptionUniv Estadual Paulista, Dept Mat Estat & Comp, BR-19060900 P Prudente, SP, Brazil-
Formato: dc.format1777-+-
Idioma: dc.languageen-
Publicador: dc.publisherAssoc Computing Machinery-
Relação: dc.relationApplied Computing 2008, Vols 1-3-
???dc.source???: dc.sourceWeb of Science-
Palavras-chave: dc.subjectGenetic algorithms-
Palavras-chave: dc.subjectMulti-population-
Palavras-chave: dc.subjectLot sizing-
Palavras-chave: dc.subjectScheduling-
Palavras-chave: dc.subjectSoft drink company-
Título: dc.titleEvaluating Genetic Algorithms with Different Population Structures on a Lot Sizing and Scheduling Problem-
Aparece nas coleções:Repositório Institucional - Unesp

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