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Improved mathematical model and bounds for the crop rotation scheduling problem with adjacency constraints

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  • Regis Mauri, Geraldo

Abstract

The Crop Rotation Scheduling Problem (CRSP) consists of alternating crops in neighboring plots during a period of time in order to find a planting schedule that satisfies a particular objective subject to some constraints such as the non-simultaneous cultivation of crops from the same botanical family in neighboring plots. In this work, some assumptions are proposed to improve a mathematical model presented in the literature, making it more general and easier to be solved by a commercial solver. In addition, five different relaxation approaches are proposed to find bounds and solutions for the CRSP. A detailed set of instances is also proposed, and a column generation procedure presented in the literature is implemented in order to perform a fair comparison of results. Computational experiments were performed indicating the improvements provided by the new model and the capability of some relaxation methods to generate high-quality solutions and bounds for the CRSP.

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  • 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.
    • Handle: RePEc:eee:ejores:v:278:y:2019:i:1:p:120-135
    DOI: 10.1016/j.ejor.2019.04.016
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    References listed on IDEAS

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    1. Brankatschk, Gerhard & Finkbeiner, Matthias, 2015. "Modeling crop rotation in agricultural LCAs — Challenges and potential solutions," Agricultural Systems, Elsevier, vol. 138(C), pages 66-76.
    2. Mauri, Geraldo Regis & Lorena, Luiz Antonio Nogueira, 2012. "A column generation approach for the unconstrained binary quadratic programming problem," European Journal of Operational Research, Elsevier, vol. 217(1), pages 69-74.
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    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. Jaehn, Florian, 2016. "Sustainable Operations," European Journal of Operational Research, Elsevier, vol. 253(2), pages 243-264.
    6. Alfandari, Laurent & Plateau, Agnès & Schepler, Xavier, 2015. "A branch-and-price-and-cut approach for sustainable crop rotation planning," European Journal of Operational Research, Elsevier, vol. 241(3), pages 872-879.
    7. dos Santos, Lana Mara R. & Costa, Alysson M. & Arenales, Marcos N. & Santos, Ricardo Henrique S., 2010. "Sustainable vegetable crop supply problem," European Journal of Operational Research, Elsevier, vol. 204(3), pages 639-647, August.
    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.
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    Cited by:

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    2. Mariana Escallón-Barrios & Daniel Castillo-Gomez & Jorge Leal & Carlos Montenegro & Andrés L. Medaglia, 2022. "Improving harvesting operations in an oil palm plantation," Annals of Operations Research, Springer, vol. 314(2), pages 411-449, July.
    3. Deininger,Klaus W. & Ali,Daniel Ayalew & Kussul,Nataliia & Lavreniuk,Mykola & Nivievskyi,Oleg, 2020. "Using Machine Learning to Assess Yield Impacts of Crop Rotation : Combining Satellite and Statistical Data for Ukraine," Policy Research Working Paper Series 9306, The World Bank.
    4. Fuchigami, Helio Yochihiro & Tuni, Andrea & Barbosa, Luísa Queiroz & Severino, Maico Roris & Rentizelas, Athanasios, 2021. "Supporting Brazilian smallholder farmers decision making in supplying institutional markets," European Journal of Operational Research, Elsevier, vol. 295(1), pages 321-335.

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