Abstract
Agricultural supply chains for fresh products exhibit higher levels of variability than those exhibited by other agri-food supply chains for products with longer shelf lives such as grains, cotton, or frozen foods. This variability takes different forms; chief among them are price and yield variability. These factors complicate the task of the grower of deciding when and how much of each crop to plant to maximize expected profits. In this chapter we discuss mathematical models for making planting decisions that are robust to the price and yield variability of fresh foods so that growers can maximize their expected profit. As part of the chapter, a case study is presented. The case study allocates production among complementary regions using a stochastic programming approach.
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References
Ahumada, O., Hernández-Cruz, X., Ulloa, R., Peinado-Guerrero, M., Quijada, F., & Villalobos, J. R. (2023). A tactical planning model for fresh produce production considering productive potential and changing weather patterns. Biosystems Engineering, 232, 13–28.
Ahumada, O., Rene Villalobos, J. R., & Nicholas Mason, A. (2012). Tactical planning of the production and distribution of fresh agricultural products under uncertainty. Agricultural Systems, 112, 17–26. https://doi.org/10.1016/j.agsy.2012.06.002
Ahumada, O., & Villalobos, J. R. (2009). Application of planning models in the agri-food supply chain: A review. European Journal of Operational Research, 196, 1–20. https://doi.org/10.1016/j.ejor.2008.02.014
Ahumada, O., & Villalobos, J. R. (2011). A tactical model for planning the production and distribution of fresh produce. Annals of Operations Research, 190(1), 339–358. https://doi.org/10.1007/s10479-009-0614-4
Allaoui, H., Guo, Y., Choudhary, A., & Bloemhof, J. (2018). Sustainable agro-food supply chain design using two-stage hybrid multi-objective decision-making approach. Computers and Operations Research, 89, 369–384. https://doi.org/10.1016/j.cor.2016.10.012
Birge, J. R., & Louveaux, F. (1997). Two-stage linear recourse problems. In Introduction to stochastic programming (pp. 155–197). Springer. https://doi.org/10.1007/0-387-22618-4_5
Birthal, P. S., & Hazrana, J. (2019). Crop diversification and resilience of agriculture to climatic shocks: Evidence from India. Agricultural Systems, 173(October 2018), 345–354. https://doi.org/10.1016/j.agsy.2019.03.005
Boyabatli, O., Nasiry, J., & Zhou, Y. H. (2019). Crop planning in sustainable agriculture: Dynamic farmland allocation in the presence of crop rotation benefits. Management Science, 65(5), 2060–2076. https://doi.org/10.1287/mnsc.2018.3044
Flores, H., & Villalobos, J. R. (2018). A modeling framework for the strategic design of local fresh-food systems. Agricultural Systems, 161, 1–15. https://doi.org/10.1016/j.agsy.2017.12.001
Flores, H., & Villalobos, J. R. (2020). A stochastic planning framework for the discovery of complementary, agricultural systems. European Journal of Operational Research, 280(2), 707–729. https://doi.org/10.1016/j.ejor.2019.07.053
Flores, H., Villalobos, J. R., Ahumada, O., Uchanski, M., Meneses, C., & Sanchez, O. (2019). Use of supply chain planning tools for efficiently placing small growers into high-value, vegetable markets. Computers and Electronics in Agriculture, 157, 205–217. https://doi.org/10.1016/j.compag.2018.12.050
Galal, N. M., & El-Kilany, K. S. (2016). Sustainable agri-food supply chain with uncertain demand and lead time. International Journal of Simulation Modelling, 15(3), 485–496.
Gaupp, F., Hall, J., Mitchell, D., & Dadson, S. (2019). Increasing risks of multiple breadbasket failure under 1.5 and 2 °C global warming. Agricultural Systems, 175(May), 34–45. https://doi.org/10.1016/j.agsy.2019.05.010
Glen, J. J. (1987). Mathematical models in farm planning: A survey. Operations Research, 35, 641–666. https://doi.org/10.1287/opre.35.5.641
Hajimirzajan, A., Vahdat, M., Sadegheih, A., Shadkam, E., & Bilali, H. E. (2021). An integrated strategic framework for large-scale crop planning: Sustainable climate-smart crop planning and agri-food supply chain management. Sustainable Production and Consumption, 26, 709–732. https://doi.org/10.1016/j.spc.2020.12.016
Hernández-Cruz, X., Villalobos, J. R., Runger, G., & Neal, G. (2022). Layered market intelligence system. Transportation Research Procedia, 67, 31–38. https://doi.org/10.1016/j.trpro.2022.12.032
Kamble, S. S., Gunasekaran, A., & Gawankar, S. A. (2020). Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications. International Journal of Production Economics, 219, 179–194. https://doi.org/10.1016/j.ijpe.2019.05.022
Lee, H. L., Padmanabhan, V., & Whang, S. (1997). The Bullwhip Effect In Supply Chains. Sloan Management Review, 38(3), 93–102.
Mason, A. N., & Villalobos, J. R. (2015). Coordination of perishable crop production using auction mechanisms. Agricultural Systems, 138, 18–30.
Parfitt, J., Barthel, M., & Macnaughton, S. (2010). Food waste within food supply chains: Quantification and potential for change to 2050. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1554), 3065–3081.
Peinado-Guerrero, M., & Villalobos, J. R. (2022). Technology-enabled, rapid-response fresh food supply chains: A paradigm and case study. Transportation Research Procedia, 67, 39–45. https://doi.org/10.1016/j.trpro.2022.12.033
Ulloa, R. (2022). Development of tools for planning and coordinating the production of small farmers as a response to market opportunities. Doctoral dissertation, Arizona State University.
Ulloa, R., & Villalobos, J. R. (2022). Use of real options for the coordination of a coalition of small growers with a buyer. Available at SSRN 4196515. https://doi.org/10.2139/ssrn.4196515
Vassalos, M., Dillon, C. R., & Coolong, T. (2013). Optimal land allocation and production timing for fresh vegetable growers under price and production uncertainty. Journal of Agricultural and Applied Economics, 45, 683–699. https://doi.org/10.1017/s1074070800005204
Villa, G., Adenso-DÃaz, B., & Lozano, S. (2019). An analysis of geographic and product diversification in crop planning strategy. Agricultural Systems, 174(December 2018), 117–124. https://doi.org/10.1016/j.agsy.2019.05.006
Villalobos, J. R., Soto-Silva, W. E., González-Araya, M. C., & González-Ramirez, R. G. (2019). Research directions in technology development to support real-time decisions of fresh produce logistics: A review and research agenda. Computers and Electronics in Agriculture, 167, 105092. https://doi.org/10.1016/j.compag.2019.105092
Zhao, C., Liu, B., Xiao, L., Hoogenboom, G., Boote, K. J., Kassie, B. T., ... & Asseng, S. (2019). A SIMPLE crop model. European Journal of Agronomy, 104, 97–106.
Zuurbier, P. J. P. (1999). Supply chain management in the fresh produce industry: A mile to go? Europe, 30, 20–30.
Acknowledgments
This work was partially supported by the Foundation for Food and Agriculture Research [Award Number CA18-SS-0000000116].
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Peinado-Guerrero, M. et al. (2024). Managing Risk in Fresh Produce Planning Considering Price Variability, Yield Variability, and Regional Complementarity. In: Albornoz, V.M., Mac Cawley, A., Plà -Aragonés, L.M. (eds) Optimization Under Uncertainty in Sustainable Agriculture and Agrifood Industry. Springer, Cham. https://doi.org/10.1007/978-3-031-49740-7_5
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