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Markov Decision Processes to Model Livestock Systems

In: Handbook of Operations Research in Agriculture and the Agri-Food Industry

Author

Listed:
  • Lars Relund Nielsen

    (Aarhus University)

  • Anders Ringgaard Kristensen

    (University of Copenhagen)

Abstract

Livestock farming problems are often sequential in nature. For instance at a specific time instance the decision on whether to replace an animal or not is based on known information and expectation about the future. At the next decision epoch updated information is available and the decision choice is re-evaluated. As a result Markov decision processes (MDPs) have been used to model livestock decision problems over the last decades. The objective of this chapter is to review the increasing amount of papers using MDPs to model livestock farming systems and provide an overview over the recent advances within this branch of research. Moreover, theory and algorithms for solving both ordinary and hierarchical MDPs are given and possible software for solving MDPs are considered.

Suggested Citation

  • Lars Relund Nielsen & Anders Ringgaard Kristensen, 2015. "Markov Decision Processes to Model Livestock Systems," International Series in Operations Research & Management Science, in: Lluis M. Plà-Aragonés (ed.), Handbook of Operations Research in Agriculture and the Agri-Food Industry, edition 127, chapter 0, pages 419-454, Springer.
    • Handle: RePEc:spr:isochp:978-1-4939-2483-7_19
    DOI: 10.1007/978-1-4939-2483-7_19
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    Cited by:

    1. Kulkarni, Pranav S. & Haijema, Rene & Hogeveen, Henk & Steeneveld, Wilma & Mourits, Monique C.M., 2024. "Economic impacts of constrained replacement heifer supply in dairy herds," Agricultural Systems, Elsevier, vol. 217(C).
    2. 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.

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