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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

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

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Autor(es):
Florentino, Helenice de Oliveira [1] ; Irawan, Chandra [2] ; Aliano, Angelo Filho [3] ; Jones, Dylan F. [2] ; Cantane, Daniela Renata [1] ; Nervis, Jonis Jecks [4]
Número total de Autores: 6
Afiliação do(s) autor(es):
[1] UNESP Univ Estadual Paulista, Dept Biostat, Botucatu, SP - Brazil
[2] Univ Portsmouth, Dept Math, Ctr Operat Res & Logist, Portsmouth, Hants - England
[3] Fed Technol Univ Parana, Acad Dept Math, Apucarana, PR - Brazil
[4] UNESP Univ Estadual Paulista, Energy Agr, FCA, Botucatu, SP - Brazil
Número total de Afiliações: 4
Tipo de documento: Artigo Científico
Fonte: ANNALS OF OPERATIONS RESEARCH; v. 267, n. 1-2, SI, p. 153-177, AUG 2018.
Citações Web of Science: 3
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. (AU)

Processo FAPESP: 13/06035-0 - Problemas do corte multiobjetivo inteiro
Beneficiário:Angelo Aliano Filho
Linha de fomento: Bolsas no Brasil - Doutorado
Processo FAPESP: 14/01604-0 - Metodologia multiobjetivo para otimização de processos em energias renováveis
Beneficiário:Helenice de Oliveira Florentino Silva
Linha de fomento: Bolsas no Exterior - Pesquisa
Processo FAPESP: 14/04353-8 - Otimização multiobjetivo aplicada aos processos de aproveitamento da biomassa da cana-de-açúcar para geração de energia
Beneficiário:Daniela Renata Cantane
Linha de fomento: Auxílio à Pesquisa - Pesquisador Visitante - Internacional