Methodology And Computing In Applied Probability

, Volume 3, Issue 2, pp 199–214

Markov Decision Processes with a Constraint on the Asymptotic Failure Rate

  • M. Boussemart
  • T. Bickard
  • N. Limnios
Article

DOI: 10.1023/A:1012209311286

Cite this article as:
Boussemart, M., Bickard, T. & Limnios, N. Methodology and Computing in Applied Probability (2001) 3: 199. doi:10.1023/A:1012209311286

Abstract

In this paper, we introduce a Markov decision model with absorbing states and a constraint on the asymptotic failure rate. The objective is to find a stationary policy which minimizes the infinite horizon expected average cost, given that the system never fails. Using Perron-Frobenius theory of non-negative matrices and spectral analysis, we show that the problem can be reduced to a linear programming problem. Finally, we apply this method to a real problem for an aeronautical system.

constrained Markov decision processasymptotic failure rateprimitive matriceslinear programming

Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • M. Boussemart
    • 1
    • 2
  • T. Bickard
    • 2
  • N. Limnios
    • 1
  1. 1.Equipe de Mathématiques AppliquéesUniversité de Technologie de CompiègneCompiègneFrance
  2. 2.Snecma Control SystemsVillarocheFrance