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.
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MathWorks Inc. http://www.matlab.com.
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Oracle http://www.java.com/.
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R Development Core Team http://www.R-project.org/.
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Acknowledgements
The authors are grateful to Dr. Anna-Maija Heikkilä, MTT Economic Research, for her valuable information about several of the Finnish models referenced.
This chapter has been compiled with support from The Danish Council for Strategic Research (The PigIT project, Grant number 11-116191).
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Nielsen, L.R., Kristensen, A.R. (2015). Markov Decision Processes to Model Livestock Systems. In: Plà-Aragonés, L. (eds) Handbook of Operations Research in Agriculture and the Agri-Food Industry. International Series in Operations Research & Management Science, vol 224. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2483-7_19
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