IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v309y2023i1p330-344.html
   My bibliography  Save this article

Multi-objective optimization for integrated sugarcane cultivation and harvesting planning

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221722009778
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2022.12.029?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Matthias Ehrgott, 2005. "Multicriteria Optimization," Springer Books, Springer, edition 0, number 978-3-540-27659-3, January.
    10. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Helenice de O. Florentino & Dylan F. Jones & Chandra Ade Irawan & Djamila Ouelhadj & Banafesh Khosravi & Daniela R. Cantane, 2022. "An optimization model for combined selecting, planting and harvesting sugarcane varieties," Annals of Operations Research, Springer, vol. 314(2), pages 451-469, July.
    2. 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.
    3. Tuğçe Taşkıner & Bilge Bilgen, 2021. "Optimization Models for Harvest and Production Planning in Agri-Food Supply Chain: A Systematic Review," Logistics, MDPI, vol. 5(3), pages 1-27, August.
    4. 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.
    5. Víctor M. Albornoz & Gabriel E. Zamora, 2021. "Decomposition-based heuristic for the zoning and crop planning problem with adjacency constraints," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 248-265, April.
    6. Víctor M. Albornoz & Lia C. Araneda & Rodrigo Ortega, 2022. "Planning and scheduling of selective harvest with management zones delineation," Annals of Operations Research, Springer, vol. 316(2), pages 873-890, September.
    7. Jitka JANOVÁ, 2014. "Crop plan optimization under risk on a farm level in the Czech Republic," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 60(3), pages 123-132.
    8. Kusumastuti, Ratih Dyah & Donk, Dirk Pieter van & Teunter, Ruud, 2016. "Crop-related harvesting and processing planning: a review," International Journal of Production Economics, Elsevier, vol. 174(C), pages 76-92.
    9. Kamal Lamsal & Philip C. Jones & Barrett W. Thomas, 2017. "Sugarcane Harvest Logistics in Brazil," Transportation Science, INFORMS, vol. 51(2), pages 771-789, May.
    10. Regis Mauri, Geraldo, 2019. "Improved mathematical model and bounds for the crop rotation scheduling problem with adjacency constraints," European Journal of Operational Research, Elsevier, vol. 278(1), pages 120-135.
    11. Víctor M. Albornoz & Marcelo I. Véliz & Rodrigo Ortega & Virna Ortíz-Araya, 2020. "Integrated versus hierarchical approach for zone delineation and crop planning under uncertainty," Annals of Operations Research, Springer, vol. 286(1), pages 617-634, March.
    12. Wishon, C. & Villalobos, J.R. & Mason, N. & Flores, H. & Lujan, G., 2015. "Use of MIP for planning temporary immigrant farm labor force," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 25-33.
    13. Camila de Lima & Antonio Roberto Balbo & Thiago Pedro Donadon Homem & Helenice de Oliveira Florentino Silva, 2017. "A hybrid approach combining interior-point and branch-and-bound methods applied to the problem of sugar cane waste," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(2), pages 147-164, February.
    14. Seyyed-Mahdi Hosseini-Motlagh & Mohammad Reza Ghatreh Samani & Firoozeh Abbasi Saadi, 2021. "Strategic optimization of wheat supply chain network under uncertainty: a real case study," Operational Research, Springer, vol. 21(3), pages 1487-1527, September.
    15. Bocca, Felipe Ferreira & Rodrigues, Luiz Henrique Antunes & Arraes, Nilson Antonio Modesto, 2015. "When do I want to know and why? Different demands on sugarcane yield predictions," Agricultural Systems, Elsevier, vol. 135(C), pages 48-56.
    16. Gómez-Lagos, Javier E. & González-Araya, Marcela C. & Soto-Silva, Wladimir E. & Rivera-Moraga, Masly M., 2021. "Optimizing tactical harvest planning for multiple fruit orchards using a metaheuristic modeling approach," European Journal of Operational Research, Elsevier, vol. 290(1), pages 297-312.
    17. Ahumada, Omar & Rene Villalobos, J. & Nicholas Mason, A., 2012. "Tactical planning of the production and distribution of fresh agricultural products under uncertainty," Agricultural Systems, Elsevier, vol. 112(C), pages 17-26.
    18. 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.
    19. Yichen Lu & Chao Yang & Jun Yang, 2022. "A multi-objective humanitarian pickup and delivery vehicle routing problem with drones," Annals of Operations Research, Springer, vol. 319(1), pages 291-353, December.
    20. Ba, Birome Holo & Prins, Christian & Prodhon, Caroline, 2016. "Models for optimization and performance evaluation of biomass supply chains: An Operations Research perspective," Renewable Energy, Elsevier, vol. 87(P2), pages 977-989.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:309:y:2023:i:1:p:330-344. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.