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Optimizing pig marketing decisions under price fluctuations

Author

Listed:
  • Reza Pourmoayed

    (Aarhus University)

  • Lars Relund Nielsen

    (Aarhus University)

Abstract

In the manufacturing of fattening pigs, pig marketing refers to a sequence of culling decisions until the production unit is empty. The profit of a production unit is highly dependent on the price of pork, the cost of feeding and the cost of buying piglets. Price fluctuations in the market consequently influence the profit, and the optimal marketing decisions may change under different price conditions. Most studies have considered pig marketing under constant price conditions. However, because price fluctuations have an influence on profit and optimal marketing decisions it is relevant to consider pig marketing under price fluctuations. In this paper we formulate a hierarchical Markov decision process with two levels which model sequential marketing decisions under price fluctuations in a pig pen. The state of the system is based on information about pork, piglet and feed prices. Moreover, the information is updated using a Bayesian approach and embedded into the hierarchical Markov decision process. The optimal policy is analyzed under different patterns of price fluctuations. We also assess the value of including price information into the model.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:annopr:v:314:y:2022:i:2:d:10.1007_s10479-020-03646-0
    DOI: 10.1007/s10479-020-03646-0
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    References listed on IDEAS

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    1. Pourmoayed, Reza & Nielsen, Lars Relund & Kristensen, Anders Ringgaard, 2016. "A hierarchical Markov decision process modeling feeding and marketing decisions of growing pigs," European Journal of Operational Research, Elsevier, vol. 250(3), pages 925-938.
    2. Roemen, J.H.J. & de Klein, S.J., 1999. "An optimal marketing strategy for porkers with differences in growth rates and dependent prices," Research Memorandum 781, Tilburg University, School of Economics and Management.
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    8. Nielsen, Lars Relund & Kristensen, Anders Ringgaard, 2006. "Finding the K best policies in a finite-horizon Markov decision process," European Journal of Operational Research, Elsevier, vol. 175(2), pages 1164-1179, December.
    9. Roemen, J.H.J. & de Klein, S.J., 1999. "An optimal marketing strategy for porkers with differences in growth rates and dependent prices," Other publications TiSEM 0a7dca18-72e9-4e53-b811-a, Tilburg University, School of Economics and Management.
    10. 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.
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    Cited by:

    1. Haohao Song & Jiquan Wang & Gang Xu & Zhanwei Tian & Fei Xu & Hong Deng, 2024. "Novel Model for Pork Supply Prediction in China Based on Modified Self-Organizing Migrating Algorithm," Agriculture, MDPI, vol. 14(9), pages 1-30, September.

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