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Feature Article—Mathematical Models in Farm Planning: A Survey

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  • John J. Glen

    (University of Edinburgh, Edinburgh, Scotland)

Abstract

Farm planning has increased in complexity and importance as agriculture in the developed world has become concentrated in larger, more specialized farm units. These changes have stimulated the development of formal planning techniques based on mathematical models. Although this approach is characteristic of operations research, the profession's direct involvement in agricultural planning has been limited: much of the published work is associated with agricultural economics. In this paper, we provide an OR-oriented introduction to the problems involved in agricultural planning, particularly at the farm level. We describe the planning problems of both the crop and livestock sectors and outline the models that have been proposed for solving these problems. Researchers, and agricultural extension and advisory services, have been the main users of these models, but the widespread availability of microcomputers gives considerable scope for developing models for use by farmers.

Suggested Citation

  • John J. Glen, 1987. "Feature Article—Mathematical Models in Farm Planning: A Survey," Operations Research, INFORMS, vol. 35(5), pages 641-666, October.
    • Handle: RePEc:inm:oropre:v:35:y:1987:i:5:p:641-666
    DOI: 10.1287/opre.35.5.641
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    8. Behzadi, Golnar & O’Sullivan, Michael Justin & Olsen, Tava Lennon & Zhang, Abraham, 2018. "Agribusiness supply chain risk management: A review of quantitative decision models," Omega, Elsevier, vol. 79(C), pages 21-42.
    9. 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.
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    12. Chintapalli, Prashant, 2023. "Optimal multi-period crop procurement and distribution policy with minimum support prices," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    13. Sergio Monteleone & Edmilson Alves de Moraes & Roberto Max Protil & Brenno Tondato de Faria & Rodrigo Filev Maia, 2024. "Proposal of a Model of Irrigation Operations Management for Exploring the Factors That Can Affect the Adoption of Precision Agriculture in the Context of Agriculture 4.0," Agriculture, MDPI, vol. 14(1), pages 1-33, January.
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    15. Onur Boyabatlı & Javad Nasiry & Yangfang (Helen) Zhou, 2019. "Crop Planning in Sustainable Agriculture: Dynamic Farmland Allocation in the Presence of Crop Rotation Benefits," Management Science, INFORMS, vol. 67(5), pages 2060-2076, May.
    16. Pinçe, Çerağ & Yücesan, Enver & Bhaskara, Prithveesha Govinda, 2021. "Accurate response in agricultural supply chains," Omega, Elsevier, vol. 100(C).
    17. Susana MEJIA & Andres Ramirez HASSAN, 2016. "Determining the optimal selling time of cattle: A stochastic dynamic programming approach," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 62(11), pages 517-527.
    18. Wenbo Zhang & Wilbert Wilhelm, 2011. "OR/MS decision support models for the specialty crops industry: a literature review," Annals of Operations Research, Springer, vol. 190(1), pages 131-148, October.
    19. Wright, Rodney & Griffin, Terry W. & Guha, Gauri & Bouldin, Jennifer, 2018. "Economic Investigation of Crop Selection in the Southern Mississippi River Basin," Journal of the ASFMRA, American Society of Farm Managers and Rural Appraisers, vol. 2018.

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