IDEAS home Printed from https://ideas.repec.org/a/inm/ortrsc/v51y2017i2p771-789.html
   My bibliography  Save this article

Sugarcane Harvest Logistics in Brazil

Author

Listed:
  • Kamal Lamsal

    (School of Business, Emporia State University, Emporia, Kansas 66801)

  • Philip C. Jones

    (Department of Management Science, University of Iowa, Iowa City, Iowa 52242)

  • Barrett W. Thomas

    (Department of Management Science, University of Iowa, Iowa City, Iowa 52242)

Abstract

Sugar mills in Brazil represent significant capital investments. To maintain appropriate returns on their investment, sugar companies seek to run the mills at capacity over the entire nine months of the sugarcane harvest season. Because the sugar content of cane degrades considerably once it is cut, maintaining inventories of cut cane is undesirable. Instead, mills want to coordinate the arrival of cut cane with production. In this paper, we present a model of the sugarcane harvest logistics problem in Brazil. We introduce a series of valid inequalities for the model, and we introduce heuristics for finding an initial feasible solution and for lifting the lower bound. Computational results demonstrate the effectiveness of the inequalities and heuristics. In addition, we explore the value of allowing trucks to serve multiple rather than single locations and demonstrate the value of allowing the harvest speed to vary.

Suggested Citation

  • Kamal Lamsal & Philip C. Jones & Barrett W. Thomas, 2017. "Sugarcane Harvest Logistics in Brazil," Transportation Science, INFORMS, vol. 51(2), pages 771-789, May.
    • Handle: RePEc:inm:ortrsc:v:51:y:2017:i:2:p:771-789
    DOI: 10.1287/trsc.2015.0650
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/trsc.2015.0650
    Download Restriction: no
    File URL: https://libkey.io/10.1287/trsc.2015.0650?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
    ---><---

    References listed on IDEAS

    as
    1. Verena Schmid & Karl F. Doerner & Richard F. Hartl & Martin W. P. Savelsbergh & Wolfgang Stoecher, 2009. "A Hybrid Solution Approach for Ready-Mixed Concrete Delivery," Transportation Science, INFORMS, vol. 43(1), pages 70-85, February.
    2. Earl O. Heady, 1954. "Simplified Presentation and Logical Aspects of Linear Programming Technique," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 36(5), pages 1035-1048.
    3. A J Higgins & L A Laredo, 2006. "Improving harvesting and transport planning within a sugar value chain," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(4), pages 367-376, April.
    4. Martin Durbin & Karla Hoffman, 2008. "OR PRACTICE---The Dance of the Thirty-Ton Trucks: Dispatching and Scheduling in a Dynamic Environment," Operations Research, INFORMS, vol. 56(1), pages 3-19, February.
    5. Neves, Marcos Fava & Gustavo Trombin, Vinicius & Alberto Consoli, Matheus, 2010. "Measurement of Sugar Cane Chain in Brazil," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 13(3), pages 1-18, September.
    6. Salassi, Michael E. & Garcia, Mercedes & Breaux, Janis B. & No, Sung Chul, 2004. "Impact of Sugarcane Delivery Schedule on Product Value at Raw Sugar Factories," Journal of Agribusiness, Agricultural Economics Association of Georgia, vol. 22(1), pages 1-15.
    7. Higgins, Andrew, 2006. "Scheduling of road vehicles in sugarcane transport: A case study at an Australian sugar mill," European Journal of Operational Research, Elsevier, vol. 170(3), pages 987-1000, May.
    8. Rafael Paiva & Reinaldo Morabito, 2009. "An optimization model for the aggregate production planning of a Brazilian sugar and ethanol milling company," Annals of Operations Research, Springer, vol. 169(1), pages 117-130, July.
    9. McConnell, Michael & Dohlman, Erik & Haley, Stephen L., 2010. "World Sugar Price Volatility Intensified by Market and Policy Factors," Amber Waves:The Economics of Food, Farming, Natural Resources, and Rural America, United States Department of Agriculture, Economic Research Service, pages 1-8.
    10. Timothy J. Lowe & Paul V. Preckel, 2004. "Decision Technologies for Agribusiness Problems: A Brief Review of Selected Literature and a Call for Research," Manufacturing & Service Operations Management, INFORMS, vol. 6(3), pages 201-208.
    11. Jeffrey W. Ohlmann & Michael J. Fry & Barrett W. Thomas, 2008. "Route Design for Lean Production Systems," Transportation Science, INFORMS, vol. 42(3), pages 352-370, August.
    12. 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.
    13. 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.
    14. Andrew Higgins & Steve Postma, 2004. "Australian Sugar Mills Optimise Siding Rosters to Increase Profitability," Annals of Operations Research, Springer, vol. 128(1), pages 235-249, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Juliana Carneiro & Matthew A. Cole & Eric Strobl, 2024. "Foetal Exposure to Air Pollution and Students' Cognitive Performance: Evidence from Agricultural Fires in Brazil," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(1), pages 156-186, February.

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Jahantab, Mahboubeh & Abbasi, Babak & Le Bodic, Pierre, 2023. "Farmland allocation in the conversion from conventional to organic farming," European Journal of Operational Research, Elsevier, vol. 311(3), pages 1103-1119.
    7. Chintapalli, Prashant & Tang, Christopher S., 2022. "The implications of crop minimum support price in the presence of myopic and strategic farmers," European Journal of Operational Research, Elsevier, vol. 300(1), pages 336-349.
    8. 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.
    9. 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.
    10. 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.
    11. Lodree Jr., Emmett J. & Uzochukwu, Benedict M., 2008. "Production planning for a deteriorating item with stochastic demand and consumer choice," International Journal of Production Economics, Elsevier, vol. 116(2), pages 219-232, December.
    12. Omar Ahumada & J. Villalobos, 2011. "A tactical model for planning the production and distribution of fresh produce," Annals of Operations Research, Springer, vol. 190(1), pages 339-358, October.
    13. Chong Wang & Xu Chen, 2017. "Option pricing and coordination in the fresh produce supply chain with portfolio contracts," Annals of Operations Research, Springer, vol. 248(1), pages 471-491, January.
    14. 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.
    15. Soto-Silva, Wladimir E. & Nadal-Roig, Esteve & González-Araya, Marcela C. & Pla-Aragones, Lluis M., 2016. "Operational research models applied to the fresh fruit supply chain," European Journal of Operational Research, Elsevier, vol. 251(2), pages 345-355.
    16. Nabeshima, Kaoru & Michida, Etsuyo, 2017. "Trend in tea trade and the role of supply chain," IDE Discussion Papers 644, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    17. 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.
    18. Sara Rodríguez & Lluis Plà & Javier Faulin, 2014. "New opportunities in operations research to improve pork supply chain efficiency," Annals of Operations Research, Springer, vol. 219(1), pages 5-23, August.
    19. Ferrer, Juan-Carlos & Mac Cawley, Alejandro & Maturana, Sergio & Toloza, Sergio & Vera, Jorge, 2008. "An optimization approach for scheduling wine grape harvest operations," International Journal of Production Economics, Elsevier, vol. 112(2), pages 985-999, April.
    20. 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.

    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:inm:ortrsc:v:51:y:2017:i:2:p:771-789. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.