MARKOVIAN DECISION PROCESS TO FIND OPTIMAL POLICIES IN THE MANAGEMENT OF AN ORANGE FARM

Authors

  • Juan Manuel Izar Landeta Facultad de Ingeniería, Universidad Autónoma de San Luis Potosí
  • Carmen Berenice Ynzunza Corté Universidad Tecnológica de Querétaro,
  • Héctor Méndez Azú Facultad de Ingeniería, Universidad Autónoma de San Luis Potosí

Keywords:

Markovian decision process, Markov chains, Optimization, Policy iteration, Linear programming

Abstract

This paper presents the application of a Markovian decision process to define the optimal policy in the case of an orange farm
management.
The problem has been proposed to be solved with two approaches: policy iteration and linear programming, which have been formulated
in first instance without discount factor and then applying various discount factors ranging from 0.5 to 0.9. The policy iteration
methodology has been more efficient than linear programming, since it requires fewer calculations to achieve the optimal solution.
In all cases the result has been that the optimal policy is to better take care the orange farm to maximize economic benefits, which would
reach an amount of 431 Mexican pesos per orange tree each year

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Published

2023-05-01

How to Cite

Izar Landeta, J. M., Ynzunza Corté, C. B., & Méndez Azú, H. (2023). MARKOVIAN DECISION PROCESS TO FIND OPTIMAL POLICIES IN THE MANAGEMENT OF AN ORANGE FARM. Investigación Operacional, 35(1). Retrieved from https://revistas.uh.cu/invoperacional/article/view/4726

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