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Exact and heuristic methods to solve a bi-objective problem of sustainable cultivation

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Resumo:This work proposes a binary nonlinear bi-objective optimization model for the problem of planning the sustainable cultivation of crops. The solution to the problem is a planting schedule for crops to be cultivated in predefined plots, in order to minimize the possibility of pest proliferation and maximize the profit of this process. Biological constraints were also considered. Exact methods, based on the nonlinear model and on a linearization of that model were proposed to generate Pareto optimal solutions for the problem of sustainable cultivation, along with a metaheuristic approach for the problem based on a genetic algorithm and on constructive heuristics. The methods were tested using semi-randomly generated instances to simulate real situations. According to the experimental results, the exact methodologies performed favorably for small and medium size instances. The heuristic method was able to potentially determine Pareto optimal solutions of good quality, in a reduced computational time, even for high dimension instances. Therefore, the mathematical models and the methods proposed may support a powerful methodology for this complex decision-making problem.
Autores principais:Filho, Angelo Aliano
Outros Autores:Florentino, Helenice de Oliveira; Pato, Margarida Vaz; Poltroniere, Sônia Cristina; Costa, Fernando da Silva
Assunto:Multi-Objective Optimization Genetic Algorithm Constructive Heuristics and Sustainability
Ano:2022
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Universidade de Lisboa
Idioma:inglês
Origem:Repositório da Universidade de Lisboa
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author Filho, Angelo Aliano
author2 Florentino, Helenice de Oliveira
Pato, Margarida Vaz
Poltroniere, Sônia Cristina
Costa, Fernando da Silva
author2_role author
author
author
author
author_facet Filho, Angelo Aliano
Florentino, Helenice de Oliveira
Pato, Margarida Vaz
Poltroniere, Sônia Cristina
Costa, Fernando da Silva
author_role author
contributor_name_str_mv Repositório Científico de Acesso Aberto da ULisboa
country_str PT
creators_json_txt [{\"Person.name\":\"Filho, Angelo Aliano\"},{\"Person.name\":\"Florentino, Helenice de Oliveira\"},{\"Person.name\":\"Pato, Margarida Vaz\"},{\"Person.name\":\"Poltroniere, Sônia Cristina\"},{\"Person.name\":\"Costa, Fernando da Silva\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Repositório Científico de Acesso Aberto da ULisboa
datacite.creators.creator.creatorName.fl_str_mv Filho, Angelo Aliano
Florentino, Helenice de Oliveira
Pato, Margarida Vaz
Poltroniere, Sônia Cristina
Costa, Fernando da Silva
datacite.date.Accepted.fl_str_mv 2022-01-01T00:00:00Z
datacite.date.available.fl_str_mv 2024-12-12T10:58:39Z
datacite.date.embargoed.fl_str_mv 2024-12-12T10:58:39Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Multi-Objective Optimization
Genetic Algorithm
Constructive Heuristics and Sustainability
datacite.titles.title.fl_str_mv Exact and heuristic methods to solve a bi-objective problem of sustainable cultivation
dc.contributor.none.fl_str_mv Repositório Científico de Acesso Aberto da ULisboa
dc.creator.none.fl_str_mv Filho, Angelo Aliano
Florentino, Helenice de Oliveira
Pato, Margarida Vaz
Poltroniere, Sônia Cristina
Costa, Fernando da Silva
dc.date.Accepted.fl_str_mv 2022-01-01T00:00:00Z
dc.date.available.fl_str_mv 2024-12-12T10:58:39Z
dc.date.embargoed.fl_str_mv 2024-12-12T10:58:39Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://hdl.handle.net/10400.5/96256
dc.language.none.fl_str_mv eng
dc.publisher.none.fl_str_mv Springer Nature
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Multi-Objective Optimization
Genetic Algorithm
Constructive Heuristics and Sustainability
dc.title.fl_str_mv Exact and heuristic methods to solve a bi-objective problem of sustainable cultivation
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_6501
description This work proposes a binary nonlinear bi-objective optimization model for the problem of planning the sustainable cultivation of crops. The solution to the problem is a planting schedule for crops to be cultivated in predefined plots, in order to minimize the possibility of pest proliferation and maximize the profit of this process. Biological constraints were also considered. Exact methods, based on the nonlinear model and on a linearization of that model were proposed to generate Pareto optimal solutions for the problem of sustainable cultivation, along with a metaheuristic approach for the problem based on a genetic algorithm and on constructive heuristics. The methods were tested using semi-randomly generated instances to simulate real situations. According to the experimental results, the exact methodologies performed favorably for small and medium size instances. The heuristic method was able to potentially determine Pareto optimal solutions of good quality, in a reduced computational time, even for high dimension instances. Therefore, the mathematical models and the methods proposed may support a powerful methodology for this complex decision-making problem.
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eu_rights_str_mv openAccess
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id ul_11cdf2ca5c2f2637cc2ceef1815fb173
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institution Universidade de Lisboa
instname_str Universidade de Lisboa
language eng
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organization_str_mv urn:organizationAcronym:ul
person_str_mv Filho, Angelo Aliano
Florentino, Helenice de Oliveira
Pato, Margarida Vaz
Poltroniere, Sônia Cristina
Costa, Fernando da Silva
publishDate 2022
publisher.none.fl_str_mv Springer Nature
reponame_str Repositório da Universidade de Lisboa
repository_id_str urn:repositoryAcronym:ul
service_str_mv urn:repositoryAcronym:ul
spelling engSpringer Naturept_PTThis work proposes a binary nonlinear bi-objective optimization model for the problem of planning the sustainable cultivation of crops. The solution to the problem is a planting schedule for crops to be cultivated in predefined plots, in order to minimize the possibility of pest proliferation and maximize the profit of this process. Biological constraints were also considered. Exact methods, based on the nonlinear model and on a linearization of that model were proposed to generate Pareto optimal solutions for the problem of sustainable cultivation, along with a metaheuristic approach for the problem based on a genetic algorithm and on constructive heuristics. The methods were tested using semi-randomly generated instances to simulate real situations. According to the experimental results, the exact methodologies performed favorably for small and medium size instances. The heuristic method was able to potentially determine Pareto optimal solutions of good quality, in a reduced computational time, even for high dimension instances. Therefore, the mathematical models and the methods proposed may support a powerful methodology for this complex decision-making problem.application/pdfpt_PTExact and heuristic methods to solve a bi-objective problem of sustainable cultivationFilho, Angelo AlianoFlorentino, Helenice de OliveiraPato, Margarida VazPoltroniere, Sônia CristinaCosta, Fernando da SilvaHostingInstitutionOrganizationalRepositório Científico de Acesso Aberto da ULisboae-mailmailto:repositorio@reitoria.ulisboa.ptrepositorio@reitoria.ulisboa.ptISSNIsPartOf1572-9338DOIIsPartOfdoi.org/10.1007/s10479-019-03468-92024-12-12T10:58:39Z20222022-01-01T00:00:00ZHandlehttp://hdl.handle.net/10400.5/96256http://purl.org/coar/access_right/c_abf2open accessMulti-Objective OptimizationGenetic AlgorithmConstructive Heuristics and Sustainability819093 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal articlehttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorio.ulisboa.pt/bitstreams/90b73bea-7d7e-4b82-9619-6bfa5af46934/download
spellingShingle Exact and heuristic methods to solve a bi-objective problem of sustainable cultivation
Filho, Angelo Aliano
Multi-Objective Optimization
Genetic Algorithm
Constructive Heuristics and Sustainability
status SINGLETON
subject.fl_str_mv Multi-Objective Optimization
Genetic Algorithm
Constructive Heuristics and Sustainability
title Exact and heuristic methods to solve a bi-objective problem of sustainable cultivation
title_full Exact and heuristic methods to solve a bi-objective problem of sustainable cultivation
title_fullStr Exact and heuristic methods to solve a bi-objective problem of sustainable cultivation
title_full_unstemmed Exact and heuristic methods to solve a bi-objective problem of sustainable cultivation
title_short Exact and heuristic methods to solve a bi-objective problem of sustainable cultivation
title_sort Exact and heuristic methods to solve a bi-objective problem of sustainable cultivation
topic Multi-Objective Optimization
Genetic Algorithm
Constructive Heuristics and Sustainability
topic_facet Multi-Objective Optimization
Genetic Algorithm
Constructive Heuristics and Sustainability
url http://hdl.handle.net/10400.5/96256
visible 1