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Multi-objective optimization for integrated sugarcane cultivation and harvesting planning

Author

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  • Aliano Filho, Angelo
  • A． Oliveira, Washington
  • Melo, Teresa

Abstract

Sugarcane and its by-products make a relevant contribution to the world economy. In particular, the sugar-energy industry is affected by the timing of sugarcane cultivation and harvesting from which sucrose and bio-energy are produced. We address this issue by proposing a mixed-integer non-linear programming model to schedule planting and harvesting operations for different varieties of sugarcane. The decisions to be made include the choice of sugarcane varieties to be grown on a given set of plots, the periods for their cultivation, the subsequent harvesting periods, and the type of harvesting equipment. These decisions are subject to various constraints related to matching cultivation periods with harvesting periods according to the maturity cycles of the selected sugarcane varieties, the availability of harvesting machinery, the demand for sucrose and fiber, and further technical requirements. The tactical cultivation and harvesting plans to be determined account for three conflicting objectives, namely maximization of the total sucrose and fiber production, minimization of the total time devoted to harvesting, and minimization of the total cost of transporting the harvesting equipment. We develop a tailored exact method based on the augmented Chebyshev scalarization technique extended with a mechanism for identifying an initial feasible integer solution that greatly helps reduce the computational effort for obtaining Pareto-optimal solutions. Our computational study with instances that reflect the current cultivation and harvesting practices in Brazil demonstrate the effectiveness of the proposed methodology. In addition, a comparative analysis reveals the trade-offs achieved by alternative planting and harvesting schedules, thereby facilitating the decision-making process.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:309:y:2023:i:1:p:330-344
    DOI: 10.1016/j.ejor.2022.12.029
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    References listed on IDEAS

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    1. Colin, Emerson C., 2009. "Mathematical programming accelerates implementation of agro-industrial sugarcane complex," European Journal of Operational Research, Elsevier, vol. 199(1), pages 232-235, November.
    2. Kamal Lamsal & Philip C. Jones & Barrett W. Thomas, 2017. "Sugarcane Harvest Logistics in Brazil," Transportation Science, INFORMS, vol. 51(2), pages 771-789, May.
    3. 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.
    4. Ahumada, Omar & Villalobos, J. Rene, 2009. "Application of planning models in the agri-food supply chain: A review," European Journal of Operational Research, Elsevier, vol. 196(1), pages 1-20, July.
    5. Lana dos Santos & Philippe Michelon & Marcos Arenales & Ricardo Santos, 2011. "Crop rotation scheduling with adjacency constraints," Annals of Operations Research, Springer, vol. 190(1), pages 165-180, October.
    6. H de Oliveira Florentino & M V Pato, 2014. "A bi-objective genetic approach for the selection of sugarcane varieties to comply with environmental and economic requirements," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(6), pages 842-854, June.
    7. 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.
    8. 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.
    9. Santos, Lana M.R. & Munari, Pedro & Costa, Alysson M. & Santos, Ricardo H.S., 2015. "A branch-price-and-cut method for the vegetable crop rotation scheduling problem with minimal plot sizes," European Journal of Operational Research, Elsevier, vol. 245(2), pages 581-590.
    10. Matthias Ehrgott, 2005. "Multicriteria Optimization," Springer Books, Springer, edition 0, number 978-3-540-27659-3, November.
    11. Jena, Sanjay Dominik & Poggi, Marcus, 2013. "Harvest planning in the Brazilian sugar cane industry via mixed integer programming," European Journal of Operational Research, Elsevier, vol. 230(2), pages 374-384.
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