DYNAMIC OPTIMIZATION MODEL TO CONTROL WEED INFESTATION: A MIXED-INTEGER NONLINEAR PROGRAMMING APPROACH

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Autor(es): dc.contributorUniversidade Tecnológica Federal do Paraná-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversidade Federal da Grande Dourados-
Autor(es): dc.creatorOliveira, Vilma Alves-
Autor(es): dc.creatorSilva, Geraldo Nunes-
Autor(es): dc.creatorFurlan, Marcos M.-
Autor(es): dc.creatorStiegelmeier, Elenice Weber-
Data de aceite: dc.date.accessioned2025-08-21T15:38:00Z-
Data de disponibilização: dc.date.available2025-08-21T15:38:00Z-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2021-12-31-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/246051-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/246051-
Descrição: dc.descriptionOne of the main goals of weed control is to maintain the weed population density in a equilibrium level that is below economic damages. To achieve this goal, we propose a dynamic optimization model for weed infestation control using herbicides rotation strategy. The objective is to reduce the seed bank and the use of herbicide, max-imizing the profit in a pre-determined period of time and minimizing the environmental impacts caused by excessive use of herbicides. The dynamic optimization model takes into account the decreased herbicide efficacy over time, which is due to an increase of weed resistance originated from selective pressure. The dynamic optimization problem involves integer and continuous variables modeled as a mixed-integer nonlinear programming problem (MINLP). The MINLP problem was solved by an implicit enumeration known as branch and bound method. Numerical simulations illustrated the solution of a case study for infestation control of the Bidens subalternans specie in a maize crop by interchang-ing between two classes of herbicides. The results demonstrate that our optimization model can improve the profit of farmers and has the potential to contribute for further decision-support tools in weed management that considers the resistance dynamics.-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionDepartment of Mathematics Universidade Tecnológica Federal do Paraná, PR-
Descrição: dc.descriptionDepartment of Electrical and Computer Engineering Universidade de São Paulo, SP-
Descrição: dc.descriptionDepartment of Applied Mathematics Universidade Estadual Paulista, SP-
Descrição: dc.descriptionFaculdade de Ciências Exatas e Tecnologias Universidade Federal da Grande Dourados, MS-
Descrição: dc.descriptionDepartment of Applied Mathematics Universidade Estadual Paulista, SP-
Descrição: dc.descriptionFAPESP: 18/08036-8-
Descrição: dc.descriptionFAPESP: 2013/07375-0-
Formato: dc.format175-196-
Idioma: dc.languageen-
Relação: dc.relationAdvances in Mathematical Sciences and Applications-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectdecision-support tools-
Palavras-chave: dc.subjectdynamic optimization model-
Palavras-chave: dc.subjectmixed-integer nonlinear programming-
Palavras-chave: dc.subjectweed management-
Título: dc.titleDYNAMIC OPTIMIZATION MODEL TO CONTROL WEED INFESTATION: A MIXED-INTEGER NONLINEAR PROGRAMMING APPROACH-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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