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Multi‐level hierarchic Markov processes as a framework for herd management support

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  • Anders Kristensen
  • Erik Jørgensen

Abstract

A general problem in relation to application of Markov decision processes to real world problems is the curse of dimensionality, since the size of the state space grows to prohibitive levels when information on all relevant traits of the system being modeled are included. In herd management, we face a hierarchy of decisions made at different levels with different time horizons, and the decisions made at different levels are mutually dependent. Furthermore, decisions have to be made without certainty about the future state of the system. These aspects contribute even further to the dimensionality problem. A new notion of a multi‐level hierarchic Markov process specially designed to solve dynamic decision problems involving decisions with varying time horizon has been presented. The method contributes significantly to circumvent the curse of dimensionality, and it provides a framework for general herd management support instead of very specialized models only concerned with a single decision as, for instance, replacement. The applicational perspectives of the technique are illustrated by potential examples relating to the management of a sow herd and a dairy herd. Copyright Kluwer Academic Publishers 2000

Suggested Citation

  • Anders Kristensen & Erik Jørgensen, 2000. "Multi‐level hierarchic Markov processes as a framework for herd management support," Annals of Operations Research, Springer, vol. 94(1), pages 69-89, January.
    • Handle: RePEc:spr:annopr:v:94:y:2000:i:1:p:69-89:10.1023/a:1018921201113
    DOI: 10.1023/A:1018921201113
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    Citations

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    Cited by:

    1. 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.
    2. Erik Jørgensen & Anders Kristensen & Dennis Nilsson, 2014. "Markov Limid processes for representing and solving renewal problems," Annals of Operations Research, Springer, vol. 219(1), pages 63-84, August.
    3. Lars Relund Nielsen & Erik Jørgensen & Søren Højsgaard, 2011. "Embedding a state space model into a Markov decision process," Annals of Operations Research, Springer, vol. 190(1), pages 289-309, October.
    4. Hegrenes, Agnar & Kristensen, Anders Ringgaard & Lien, Gudbrand D., 2003. "Optimal Economic Length Of Leys: A Dynamic Programming Approach," 2003 Annual Meeting, August 16-22, 2003, Durban, South Africa 25848, International Association of Agricultural Economists.
    5. Toft, Nils & Kristensen, Anders R. & Jorgensen, Erik, 2005. "A framework for decision support related to infectious diseases in slaughter pig fattening units," Agricultural Systems, Elsevier, vol. 85(2), pages 120-137, August.
    6. Kazim Topuz & Hasmet Uner & Asil Oztekin & Mehmet Bayram Yildirim, 2018. "Predicting pediatric clinic no-shows: a decision analytic framework using elastic net and Bayesian belief network," Annals of Operations Research, Springer, vol. 263(1), pages 479-499, April.
    7. 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.
    8. 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.
    9. Lan Ge & Anders Kristensen & Monique Mourits & Ruud Huirne, 2014. "A new decision support framework for managing foot-and-mouth disease epidemics," Annals of Operations Research, Springer, vol. 219(1), pages 49-62, August.
    10. Demeter, Robert Milan & Bovenhuis, Henk & Kristensen, Anders Ringgaard & Oude Lansink, Alfons G.J.M. & Meuwissen, Miranda P.M. & van Arendonk, Johan A.M., 2011. "Farm Level Economic Implications of Genetic Selection for Improving Milk Fat Composition," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114444, European Association of Agricultural Economists.

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