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

Author

Listed:
  • Helenice de Oliveira Florentino

    (UNESP - Univ Estadual Paulista)

  • Chandra Irawan

    (University of Portsmouth)

  • Angelo Filho Aliano

    (Federal Technology University of Paraná)

  • Dylan F. Jones

    (University of Portsmouth)

  • Daniela Renata Cantane

    (UNESP - Univ Estadual Paulista)

  • Jonis Jecks Nervis

    (UNESP - Univ Estadual Paulista)

Abstract

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.

Suggested Citation

  • Helenice de Oliveira Florentino & Chandra Irawan & Angelo Filho Aliano & Dylan F. Jones & Daniela Renata Cantane & Jonis Jecks Nervis, 2018. "A multiple objective methodology for sugarcane harvest management with varying maturation periods," Annals of Operations Research, Springer, vol. 267(1), pages 153-177, August.
    • Handle: RePEc:spr:annopr:v:267:y:2018:i:1:d:10.1007_s10479-017-2568-2
    DOI: 10.1007/s10479-017-2568-2
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    References listed on IDEAS

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    Cited by:

    1. Hocine, Amin & Zhuang, Zheng-Yun & Kouaissah, Noureddine & Li, Der-Chiang, 2020. "Weighted-additive fuzzy multi-choice goal programming (WA-FMCGP) for supporting renewable energy site selection decisions," European Journal of Operational Research, Elsevier, vol. 285(2), pages 642-654.
    2. Junqueira, Rogerio de Ávila Ribeiro & Morabito, Reinaldo, 2019. "Modeling and solving a sugarcane harvest front scheduling problem," International Journal of Production Economics, Elsevier, vol. 213(C), pages 150-160.
    3. Angelo Aliano Filho & Helenice Oliveira Florentino & Margarida Vaz Pato & Sônia Cristina Poltroniere & João Fernando Silva Costa, 2022. "Exact and heuristic methods to solve a bi-objective problem of sustainable cultivation," Annals of Operations Research, Springer, vol. 314(2), pages 347-376, July.
    4. Amalia Utamima & Torsten Reiners & Amir H. Ansaripoor, 2022. "Evolutionary neighborhood discovery algorithm for agricultural routing planning in multiple fields," Annals of Operations Research, Springer, vol. 316(2), pages 955-977, September.
    5. Aliano Filho, Angelo & A． Oliveira, Washington & Melo, Teresa, 2023. "Multi-objective optimization for integrated sugarcane cultivation and harvesting planning," European Journal of Operational Research, Elsevier, vol. 309(1), pages 330-344.

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