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Conclusions and Open Research Problems

  • Dirk Beyer
  • Feng Cheng
  • Suresh P. Sethi
  • Michael Taksar
Chapter
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 108)

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 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag US 2010

Authors and Affiliations

  • Dirk Beyer
    • 1
  • Feng Cheng
    • 2
  • Suresh P. Sethi
    • 3
  • Michael Taksar
    • 4
  1. 1.M-FactorSan MateoUSA
  2. 2.Federal Aviation AdministrationOffice of Performance Analysis and StrategyWashingtonUSA
  3. 3.School of Management, M/S SM30The University of Texas at DallasRichardsonUSA
  4. 4.Department of MathematicsUniversity of MissouriColumbiaUSA

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