Abstract
This note describes sufficient conditions under which total-cost and average-cost Markov decision processes (MDPs) with general state and action spaces, and with weakly continuous transition probabilities, can be reduced to discounted MDPs. For undiscounted problems, these reductions imply the validity of optimality equations and the existence of stationary optimal policies. The reductions also provide methods for computing optimal policies. The results are applied to a capacitated inventory control problem with fixed costs and lost sales.
| Original language | English |
|---|---|
| Pages (from-to) | 179-184 |
| Number of pages | 6 |
| Journal | Operations Research Letters |
| Volume | 46 |
| Issue number | 2 |
| DOIs | |
| State | Published - Mar 2018 |
Keywords
- Average cost
- Discounted
- Inventory
- Markov decision process
- Reduction
- Total cost
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