Markov Decision Processes to Model Livestock Systems

Lars Relund Nielsen () and Anders Ringgaard Kristensen ()
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Lars Relund Nielsen: Aarhus University
Anders Ringgaard Kristensen: University of Copenhagen

Chapter Chapter 19 in Handbook of Operations Research in Agriculture and the Agri-Food Industry, 2015, pp 419-454 from Springer

Abstract: 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.

Keywords: Optimal Policy; Milk Yield; Markov Decision Process; Policy Iteration; Average Reward (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/978-1-4939-2483-7_19

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