Inventory Models with Markovian Demands and Cost Functions of Polynomial Growth
Journal of Optimization Theory and Applications, Vol. 98, No. 2, pp. 281-323, August 1998
36 Pages Posted: 14 Feb 2008 Last revised: 21 Apr 2008
Abstract
This paper studies stochastic inventory problems with unbounded Markovian demands, ordering costs that are lower semicontinuous, and inventory/backlog (or surplus) costs that are lower semicontinuous with polynomial growth. Finite-horizon problems, stationary and nonstationary discounted-cost infinite-horizon problems, and stationary long-run average-cost problems are addressed. Existence of optimal Markov or feedback policies is established. Furthermore, optimality of (s, S)-type policies is proved when, in addition, the ordering cost consists of fixed and proportional cost components and the surplus cost is convex.
Keywords: Dynamic inventory models - Markov chains - dynamic programming, finite horizon, infinite horizon , cyclic demand, (s, S)-policy, inventory models, Markov process, cost with polynomial growth, average cost, ergodic problem, base-stockpolicy, incomplete information, partial observations
JEL Classification: C61, M11, D81,D83
Suggested Citation: Suggested Citation
Do you have negative results from your research you’d like to share?
Recommended Papers
-
Optimality of (s, S) Policies in Inventory Models with Markovian Demand
By Suresh Sethi and Feng Cheng
-
Average Cost Optimality in Inventory Models with Markovian Demands: A Summary
By Dirk Beyer and Suresh Sethi
-
By Feng Cheng and Suresh Sethi
-
The Classical Average-Cost Inventory Models of Iglehart and Veinott-Wagner Revisited
By Dirk Beyer and Suresh Sethi
-
Average Cost Optimality in Inventory Models with Markovian Demands and Lost Sales
By Dirk Beyer and Suresh Sethi
-
A Production-Inventory Problem under an Energy Buy-Back Program
By Frank (youhua) Chen, Suresh Sethi, ...