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Mathematical model for strategic planning optimization in the pome fruit industry

Author

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  • Catalá, Luis P.
  • Durand, Guillermo A.
  • Blanco, Aníbal M.
  • Alberto Bandoni, J.

Abstract

This paper presents a strategic planning model for optimal restructuring of a pome (pears and apples) production farm concerning varieties and planting densities. The model decides the optimal investment policy for a given farm, maximizing the net present value of business while dynamically deciding its planting structure along a given time horizon under different financing scenarios. The model constraints impose restrictions on the activities to take into account risks and cultural practices. The mathematical model corresponds to a mixed integer linear programming problem, where integer decisions are related to the minimum reconversion land unit and funding requirements.

Suggested Citation

  • Catalá, Luis P. & Durand, Guillermo A. & Blanco, Aníbal M. & Alberto Bandoni, J., 2013. "Mathematical model for strategic planning optimization in the pome fruit industry," Agricultural Systems, Elsevier, vol. 115(C), pages 63-71.
    • Handle: RePEc:eee:agisys:v:115:y:2013:i:c:p:63-71
    DOI: 10.1016/j.agsy.2012.09.010
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    References listed on IDEAS

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    1. Cittadini, E.D. & Lubbers, M.T.M.H. & de Ridder, N. & van Keulen, H. & Claassen, G.D.H., 2008. "Exploring options for farm-level strategic and tactical decision-making in fruit production systems of South Patagonia, Argentina," Agricultural Systems, Elsevier, vol. 98(3), pages 189-198, October.
    2. Ward, Lionel E. & Faris, J. Edwin, 1968. "A Stochastic Approach to Replacement Policies For Plum Trees," Monographs, University of California, Davis, Giannini Foundation, number 251953, December.
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    Cited by:

    1. Rohrig, Maren B.K. & Hardeweg, Bernd & Lentz, Wolfgang, 2018. "Efficient farming options for German apple growers under risk – a stochastic dominance approach," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 21(1).
    2. Yingxue Rao & Min Zhou & Chunxia Cao & Shukui Tan & Yan Song & Zuo Zhang & Deyi Dai & Guoliang Ou & Lu Zhang & Xin Nie & Aiping Deng & Zhuoma Cairen, 2019. "Exploring the quantitive relationship between economic benefit and environmental constraint using an inexact chance-constrained fuzzy programming based industrial structure optimization model," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 2199-2220, July.
    3. Ana Esteso & M. M. E. Alemany & Angel Ortiz & Shaofeng Liu, 2022. "Optimization model to support sustainable crop planning for reducing unfairness among farmers," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(3), pages 1101-1127, September.
    4. Ramos, Francisco López & Batres, Rafael & De-la-Cruz-Márquez, Cynthia Griselle & Anzures, Melina López, 2023. "Optimization models for nopal crop planning with land usage expansion and government subsidy," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    5. 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.
    6. 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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