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Harvest planning in the Brazilian sugar cane industry via mixed integer programming

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  • Jena, Sanjay Dominik
  • Poggi, Marcus

Abstract

This work addresses harvest planning problems that arise in the production of sugar and alcohol from sugar cane in Brazil. The planning is performed for two planning horizons, tactical and operational planning, such that the total sugar content in the harvested cane is maximized. The tactical planning comprises the entire harvest season that averages seven months. The operational planning considers a horizon from seven to thirty days. Both problems are solved by mixed integer programming. The tactical planning is well handled. The model for the operational planning extends the one for the tactical planning and is presented in detail. Valid inequalities are introduced and three techniques are proposed to speed up finding quality solutions. These include pre-processing by grouping and filtering the distance matrix between fields, hot starting with construction heuristic solutions, and dividing and sequentially solving the resulting MIP program. Experiments are run over a set of real world and artificial instances. A case study illustrates the benefits of the proposed planning.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ejores:v:230:y:2013:i:2:p:374-384
    DOI: 10.1016/j.ejor.2013.04.011
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    Cited by:

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    2. Shunyu Yao & Neng Fan & Clark Seavert & Trent Teegerstrom, 2023. "Demand-Driven Harvest Planning and Machinery Scheduling for Guayule," SN Operations Research Forum, Springer, vol. 4(1), pages 1-25, March.
    3. Yiping Jiang & Liangqi Chen & Yan Fang, 2018. "Integrated Harvest and Distribution Scheduling with Time Windows of Perishable Agri-Products in One-Belt and One-Road Context," Sustainability, MDPI, vol. 10(5), pages 1-13, May.
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    5. 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.
    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. A. Khoodaruth, 2016. "Contribution of the sugar cane industry to reduce carbon dioxide emissions in the energy sector: the case of Mauritius," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 18(6), pages 1719-1731, December.
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    9. 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.
    10. Kamal Lamsal & Philip C. Jones & Barrett W. Thomas, 2017. "Sugarcane Harvest Logistics in Brazil," Transportation Science, INFORMS, vol. 51(2), pages 771-789, May.
    11. 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.
    12. J. Contreras & H. Lara & G. Nouel-Borges, 2019. "A mixed integer nonlinear programming model for biomass production," Operational Research, Springer, vol. 19(1), pages 39-57, March.
    13. 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.
    14. 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.
    15. Adriano de Oliveira Martins & Fernando Elemar Vicente dos Anjos & Debora Oliveira da Silva, 2023. "The Lean Farm: Application of Tools and Concepts of Lean Manufacturing in Agro-Pastoral Crops," Sustainability, MDPI, vol. 15(3), pages 1-20, February.
    16. Kamal Lamsal & Philip C. Jones & Barrett W. Thomas, 2016. "Continuous time scheduling for sugarcane harvest logistics in Louisiana," International Journal of Production Research, Taylor & Francis Journals, vol. 54(2), pages 616-627, January.
    17. 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.
    18. 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.
    19. 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.
    20. 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.

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