A multiple objective methodology for sugarcane harvest management with varying maturation periods

Detalhes bibliográficos
Autor(a) principal: Florentino, Helenice de Oliveira [UNESP]
Data de Publicação: 2018
Outros Autores: Irawan, Chandra, Aliano, Angelo Filho, Jones, Dylan F., Cantane, Daniela Renata [UNESP], Nervis, Jonis Jecks [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/s10479-017-2568-2
http://hdl.handle.net/11449/178988
Resumo: This paper addresses the management of a sugarcane harvest over a multi-year planning period. A methodology to assist the harvest planning of the sugarcane is proposed in order to improve the production of POL (a measure of the amount of sucrose contained in a sugar solution) and the quality of the raw material, considering the constraints imposed by the mill such as the demand per period. An extended goal programming model is proposed for optimizing the harvest plan of the sugarcane so the harvesting point is as close as possible to the ideal, considering the constrained nature of the problem. A genetic algorithm (GA) is developed to tackle the problem in order to solve realistically large problems within an appropriate computational time. A comparative analysis between the GA and an exact method for small instances is also given in order to validate the performance of the developed model and methods. Computational results for medium and large farm instances using GA are also presented in order to demonstrate the capability of the developed method. The computational results illustrate the trade-off between satisfying the conflicting goals of harvesting as closely as possible to the ideal and making optimum use of harvesting equipment with a minimum of movement between farms. They also demonstrate that, whilst harvesting plans for small scale farms can be generated by the exact method, a meta-heuristic GA method is currently required in order to devise plans for medium and large farms.
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spelling A multiple objective methodology for sugarcane harvest management with varying maturation periodsGenetic algorithmGoal programmingMultiple objective optimizationSugarcane harvest planningThis paper addresses the management of a sugarcane harvest over a multi-year planning period. A methodology to assist the harvest planning of the sugarcane is proposed in order to improve the production of POL (a measure of the amount of sucrose contained in a sugar solution) and the quality of the raw material, considering the constraints imposed by the mill such as the demand per period. An extended goal programming model is proposed for optimizing the harvest plan of the sugarcane so the harvesting point is as close as possible to the ideal, considering the constrained nature of the problem. A genetic algorithm (GA) is developed to tackle the problem in order to solve realistically large problems within an appropriate computational time. A comparative analysis between the GA and an exact method for small instances is also given in order to validate the performance of the developed model and methods. Computational results for medium and large farm instances using GA are also presented in order to demonstrate the capability of the developed method. The computational results illustrate the trade-off between satisfying the conflicting goals of harvesting as closely as possible to the ideal and making optimum use of harvesting equipment with a minimum of movement between farms. They also demonstrate that, whilst harvesting plans for small scale farms can be generated by the exact method, a meta-heuristic GA method is currently required in order to devise plans for medium and large farms.Department of Biostatistics UNESP - Univ Estadual PaulistaDepartment of Mathematics Centre for Operational Research and Logistics University of PortsmouthAcademic Department of Mathematics Federal Technology University of ParanáEnergy in Agriculture FCA UNESP - Univ Estadual PaulistaDepartment of Biostatistics UNESP - Univ Estadual PaulistaEnergy in Agriculture FCA UNESP - Univ Estadual PaulistaUniversidade Estadual Paulista (Unesp)University of PortsmouthFederal Technology University of ParanáFlorentino, Helenice de Oliveira [UNESP]Irawan, ChandraAliano, Angelo FilhoJones, Dylan F.Cantane, Daniela Renata [UNESP]Nervis, Jonis Jecks [UNESP]2018-12-11T17:33:03Z2018-12-11T17:33:03Z2018-08-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article153-177application/pdfhttp://dx.doi.org/10.1007/s10479-017-2568-2Annals of Operations Research, v. 267, n. 1-2, p. 153-177, 2018.1572-93380254-5330http://hdl.handle.net/11449/17898810.1007/s10479-017-2568-22-s2.0-850217529712-s2.0-85021752971.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAnnals of Operations Research0,9430,943info:eu-repo/semantics/openAccess2023-12-03T06:11:06Zoai:repositorio.unesp.br:11449/178988Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:21:30.897323Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A multiple objective methodology for sugarcane harvest management with varying maturation periods
title A multiple objective methodology for sugarcane harvest management with varying maturation periods
spellingShingle A multiple objective methodology for sugarcane harvest management with varying maturation periods
Florentino, Helenice de Oliveira [UNESP]
Genetic algorithm
Goal programming
Multiple objective optimization
Sugarcane harvest planning
title_short A multiple objective methodology for sugarcane harvest management with varying maturation periods
title_full A multiple objective methodology for sugarcane harvest management with varying maturation periods
title_fullStr A multiple objective methodology for sugarcane harvest management with varying maturation periods
title_full_unstemmed A multiple objective methodology for sugarcane harvest management with varying maturation periods
title_sort A multiple objective methodology for sugarcane harvest management with varying maturation periods
author Florentino, Helenice de Oliveira [UNESP]
author_facet Florentino, Helenice de Oliveira [UNESP]
Irawan, Chandra
Aliano, Angelo Filho
Jones, Dylan F.
Cantane, Daniela Renata [UNESP]
Nervis, Jonis Jecks [UNESP]
author_role author
author2 Irawan, Chandra
Aliano, Angelo Filho
Jones, Dylan F.
Cantane, Daniela Renata [UNESP]
Nervis, Jonis Jecks [UNESP]
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
University of Portsmouth
Federal Technology University of Paraná
dc.contributor.author.fl_str_mv Florentino, Helenice de Oliveira [UNESP]
Irawan, Chandra
Aliano, Angelo Filho
Jones, Dylan F.
Cantane, Daniela Renata [UNESP]
Nervis, Jonis Jecks [UNESP]
dc.subject.por.fl_str_mv Genetic algorithm
Goal programming
Multiple objective optimization
Sugarcane harvest planning
topic Genetic algorithm
Goal programming
Multiple objective optimization
Sugarcane harvest planning
description This paper addresses the management of a sugarcane harvest over a multi-year planning period. A methodology to assist the harvest planning of the sugarcane is proposed in order to improve the production of POL (a measure of the amount of sucrose contained in a sugar solution) and the quality of the raw material, considering the constraints imposed by the mill such as the demand per period. An extended goal programming model is proposed for optimizing the harvest plan of the sugarcane so the harvesting point is as close as possible to the ideal, considering the constrained nature of the problem. A genetic algorithm (GA) is developed to tackle the problem in order to solve realistically large problems within an appropriate computational time. A comparative analysis between the GA and an exact method for small instances is also given in order to validate the performance of the developed model and methods. Computational results for medium and large farm instances using GA are also presented in order to demonstrate the capability of the developed method. The computational results illustrate the trade-off between satisfying the conflicting goals of harvesting as closely as possible to the ideal and making optimum use of harvesting equipment with a minimum of movement between farms. They also demonstrate that, whilst harvesting plans for small scale farms can be generated by the exact method, a meta-heuristic GA method is currently required in order to devise plans for medium and large farms.
publishDate 2018
dc.date.none.fl_str_mv 2018-12-11T17:33:03Z
2018-12-11T17:33:03Z
2018-08-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1007/s10479-017-2568-2
Annals of Operations Research, v. 267, n. 1-2, p. 153-177, 2018.
1572-9338
0254-5330
http://hdl.handle.net/11449/178988
10.1007/s10479-017-2568-2
2-s2.0-85021752971
2-s2.0-85021752971.pdf
url http://dx.doi.org/10.1007/s10479-017-2568-2
http://hdl.handle.net/11449/178988
identifier_str_mv Annals of Operations Research, v. 267, n. 1-2, p. 153-177, 2018.
1572-9338
0254-5330
10.1007/s10479-017-2568-2
2-s2.0-85021752971
2-s2.0-85021752971.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Annals of Operations Research
0,943
0,943
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 153-177
application/pdf
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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