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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

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

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Florentino, Helenice de Oliveira [1] ; Irawan, Chandra [2] ; Aliano, Angelo Filho [3] ; Jones, Dylan F. [2] ; Cantane, Daniela Renata [1] ; Nervis, Jonis Jecks [4]
Total Authors: 6
[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
Total Affiliations: 4
Document type: Journal article
Source: ANNALS OF OPERATIONS RESEARCH; v. 267, n. 1-2, SI, p. 153-177, AUG 2018.
Web of Science Citations: 3

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)

FAPESP's process: 13/06035-0 - Multiobjective integer cutting problems
Grantee:Angelo Aliano Filho
Support type: Scholarships in Brazil - Doctorate
FAPESP's process: 14/01604-0 - A multiobjective methodology for renewable energy
Grantee:Helenice de Oliveira Florentino Silva
Support type: Scholarships abroad - Research
FAPESP's process: 14/04353-8 - Multiobjective optimization applied to sugarcane biomass utilization for generation of energy
Grantee:Daniela Renata Cantane
Support type: Research Grants - Visiting Researcher Grant - International