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

Helenice de Oliveira Florentino, Chandra Irawan, Angelo Filho, Dylan Jones, Daniela Cantane, Jonis Nervis

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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 mea-
sure 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-o 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.
Original languageEnglish
JournalAnnals of Operations Research
Early online date30 Jun 2017
Publication statusEarly online - 30 Jun 2017


  • multiple objective optimization
  • goal programming
  • genetic algorithm
  • sugarcane harvest planning


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