A hierarchical Markov decision process modeling feeding and marketing decisions of growing pigs

Reza Pourmoayed; Lars Relund Nielsen; Anders Ringgaard Kristensen

doi:10.1016/j.ejor.2015.09.038

A hierarchical Markov decision process modeling feeding and marketing decisions of growing pigs

Reza Pourmoayed, Lars Relund Nielsen, Anders Ringgaard Kristensen

15 Citations (Scopus)

Abstract

Feeding is the most important cost in the production of growing pigs and has a direct impact on the marketing decisions, growth and the final quality of the meat. In this paper, we address the sequential decision problem of when to change the feed-mix within a finisher pig pen and when to pick pigs for marketing. We formulate a hierarchical Markov decision process with three levels representing the decision process. The model considers decisions related to feeding and marketing and finds the optimal decision given the current state of the pen. The state of the system is based on information from on-line repeated measurements of pig weights and feeding and is updated using a Bayesian approach. Numerical examples are given to illustrate the features of the proposed optimization model.

Original language	English
Journal	European Journal of Operational Research
Volume	250
Issue number	3
Pages (from-to)	925-938
Number of pages	14
ISSN	0377-2217
DOIs	https://doi.org/10.1016/j.ejor.2015.09.038
Publication status	Published - 1 May 2016

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10.1016/j.ejor.2015.09.038

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abstract = "Feeding is the most important cost in the production of growing pigs and has a direct impact on the marketing decisions, growth and the final quality of the meat. In this paper, we address the sequential decision problem of when to change the feed-mix within a finisher pig pen and when to pick pigs for marketing. We formulate a hierarchical Markov decision process with three levels representing the decision process. The model considers decisions related to feeding and marketing and finds the optimal decision given the current state of the pen. The state of the system is based on information from on-line repeated measurements of pig weights and feeding and is updated using a Bayesian approach. Numerical examples are given to illustrate the features of the proposed optimization model.",

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AU - Nielsen, Lars Relund

AU - Kristensen, Anders Ringgaard

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N2 - Feeding is the most important cost in the production of growing pigs and has a direct impact on the marketing decisions, growth and the final quality of the meat. In this paper, we address the sequential decision problem of when to change the feed-mix within a finisher pig pen and when to pick pigs for marketing. We formulate a hierarchical Markov decision process with three levels representing the decision process. The model considers decisions related to feeding and marketing and finds the optimal decision given the current state of the pen. The state of the system is based on information from on-line repeated measurements of pig weights and feeding and is updated using a Bayesian approach. Numerical examples are given to illustrate the features of the proposed optimization model.

AB - Feeding is the most important cost in the production of growing pigs and has a direct impact on the marketing decisions, growth and the final quality of the meat. In this paper, we address the sequential decision problem of when to change the feed-mix within a finisher pig pen and when to pick pigs for marketing. We formulate a hierarchical Markov decision process with three levels representing the decision process. The model considers decisions related to feeding and marketing and finds the optimal decision given the current state of the pen. The state of the system is based on information from on-line repeated measurements of pig weights and feeding and is updated using a Bayesian approach. Numerical examples are given to illustrate the features of the proposed optimization model.

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JO - European Journal of Operational Research

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A hierarchical Markov decision process modeling feeding and marketing decisions of growing pigs

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