Average Cost Optimality in Inventory Models with Markovian Demands

D. Beyer and Suresh Sethi
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D. Beyer: University of Toronto

Journal of Optimization Theory and Applications, 1997, vol. 92, issue 3, No 4, 497-526

Abstract: Abstract This paper is concerned with long-run average cost minimization of a stochastic inventory problem with Markovian demand, fixed ordering cost, and convex surplus cost. The states of the Markov chain represent different possible states of the environment. Using a vanishing discount approach, a dynamic programming equation and the corresponding verification theorem are established. Finally, the existence of an optimal state-dependent (s, S) policy is proved.

Keywords: Dynamic inventory model; Markov chain; dynamic programming; infinite horizon; long-run average cost; ergodic cost; (s; S) policy (search for similar items in EconPapers)
Date: 1997
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Citations: View citations in EconPapers (29)

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DOI: 10.1023/A:1022651322174

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