Abstract:
The exact analysis of optimal ordering policies for periodic-review perishable inventory systems is challenging because of their high-dimensional state space arising from multiple interrelated ordering decisions over many periods and age distributions of on-hand products. We develop a new marginal analysis framework to approximate this complex multiple-decision model into a single-decision model with an externality term, which internalizes the long-term impact of ordering decisions. Our externality-based approximation utilizes a constant base-stock policy; it is fast and easy to apply. Numerical experiments show that our approach provides state-dependent ordering amounts almost identical to the optimal dynamic programming-based policy.
