Conclusions and Open Research Problems

Dirk Beyer (), Feng Cheng (), Suresh Sethi and Michael Taksar ()
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Dirk Beyer: M-Factor
Feng Cheng: Office of Performance Analysis and Strategy
Michael Taksar: University of Missouri

Chapter Chapter 10 in Markovian Demand Inventory Models, 2010, pp 211-213 from Springer

Abstract: Abstract The Markovian demand approach provides a realistic way of modeling real-world demand scenarios. It allows us to relax the common assumption of demands being independent over time in the inventory literature. By associating the demand process with an underlying Markov chain, we are able to capture the effect of environmental factors that influence the demand process. Although the modeling capability is significantly enhanced by the incorporation of Markovian demands in inventory models, the simplicity of the optimal policies normally exhibited in the classical inventory problems is still preserved. Specifically, we show that the (s, S)-type policies shown to be optimal for a large class of inventory models with independent demands continue to be optimal for Markovian demand models, with one difference. That is, with Markovian demands, the (s, S) values depend on the state of the Markov process.

Keywords: Optimal Policy; Inventory Model; Markov Decision Process; Demand Process; Inventory Problem (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-0-387-71604-6_10

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DOI: 10.1007/978-0-387-71604-6_10

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