Dynamic programming (DP) is often seen in inventory control to lead to optimal ordering policies. When considering stationary demand, Value Iteration (VI) may be used to derive the best policy. In this paper, our focus is on the computational procedures to implement VI. Practical implementation requires bounding carefully the state space and demand in an adequate way. We illustrate with small cases the challenge of the implementation. We also show that handling service level constraints is not straightforward from a DP point of view. Moreover, when taking the age distribution into account for perishable products, the curse of dimensionality provides an additional challenge.
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