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An integer programming model for optimal pork marketing

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  • Jeffrey Ohlmann
  • Philip Jones

Abstract

Pork producers must determine when to sell pigs, which and how many pigs to sell, and to which packer(s) to sell them. We model the decision-making problem as a linear mixed-integer program that determines the marketing strategy that maximizes expected annual profit. By discretizing the barn population into appropriate weight and growth categories, we formulate an mixed-integer program that captures the effect of stocking space and shipping disruption on pig growth. We consider marketing to multiple packers via shipping policies reflecting operational sorting constraints. Utilizing data from Cargill Animal Nutrition, we implement the model to obtain solutions that characterize significant strategic departures from commonly-implemented industry rules-of-thumb and that possess the potential to increase profitability in an industry characterized by narrow profit margins. Copyright Springer Science+Business Media, LLC 2011

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  • Jeffrey Ohlmann & Philip Jones, 2011. "An integer programming model for optimal pork marketing," Annals of Operations Research, Springer, vol. 190(1), pages 271-287, October.
    • Handle: RePEc:spr:annopr:v:190:y:2011:i:1:p:271-287:10.1007/s10479-008-0466-3
    DOI: 10.1007/s10479-008-0466-3
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    References listed on IDEAS

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    1. McBride, William D. & Key, Nigel D., 2003. "Economic And Structural Relationships In U.S. Hog Production," Agricultural Economic Reports 33971, United States Department of Agriculture, Economic Research Service.
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    4. Jean-Paul Chavas & James Kliebenstein & Thomas D. Crenshaw, 1985. "Modeling Dynamic Agricultural Production Response: The Case of Swine Production," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 67(3), pages 636-646.
    5. Kathryn A. Boys & Ning Li & Paul V. Preckel & Allan P. Schinckel & Kenneth A. Foster, 2007. "Economic Replacement of a Heterogeneous Herd," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(1), pages 24-35.
    6. Li, Ning & Preckel, Paul V. & Foster, Kenneth A. & Schinckel, Allan P., 2003. "Analysis of Economically Optimal Nutrition and Marketing Strategies for Paylean® Usage in Hog Production," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 28(2), pages 1-15, August.
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    Cited by:

    1. Peng-Sheng YOU & Yi-Chih HSIEH, 2018. "A study of production and harvesting planning for the chicken industry," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 64(7), pages 316-327.
    2. Esteve Nadal-Roig & Lluís Miquel Plà-Aragonès & Víctor Manuel Albornoz, 2023. "Supply Chains: Planning the Transportation of Animals among Facilities," Sustainability, MDPI, vol. 15(3), pages 1-14, January.
    3. Reza Pourmoayed & Lars Relund Nielsen, 2022. "Optimizing pig marketing decisions under price fluctuations," Annals of Operations Research, Springer, vol. 314(2), pages 617-644, July.
    4. Esteve Nadal-Roig & Adela Pagès-Bernaus & Lluís M. Plà-Aragonès, 2018. "Bi-Objective Optimization Model Based on Profit and CO 2 Emissions for Pig Deliveries to the Abattoir," Sustainability, MDPI, vol. 10(6), pages 1-13, May.
    5. 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.
    6. Pourmoayed, Reza & Nielsen, Lars Relund, 2019. "An approximate dynamic programming approach for sequential pig marketing decisions at herd level," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1056-1070.

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