Sensitivity analysis and optimal ultimately stationary deterministic policies in some constrained discounted cost models

Krishnamurthy Iyer, Nandyala Hemachandra

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

We consider a discrete time Markov Decision Process (MDP) under the discounted payoff criterion in the presence of additional discounted cost constraints. We study the sensitivity of optimal Stationary Randomized (SR) policies in this setting with respect to the upper bound on the discounted cost constraint functionals.We show that such sensitivity analysis leads to an improved version of the Feinberg-Shwartz algorithm (Math Oper Res 21(4):922-945, 1996) for finding optimal policies that are ultimately stationary and deterministic.

Original languageEnglish (US)
Pages (from-to)401-425
Number of pages25
JournalMathematical Methods of Operations Research
Volume71
Issue number3
DOIs
StatePublished - Jun 1 2010
Externally publishedYes

Keywords

  • Finite models
  • Linear programming
  • Randomized policies
  • Simplicies
  • Stationary deterministic policies

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