On computing optimal policies in perishable inventory control using value iteration

As a large part of world food production spoils/expires before consumption, reduction of food waste by optimizing order policies in retail is of importance. We sketch here the computational burden of trying to obtain the optimal order quantities with the process of value iteration for a retailer situation with highly perishable products. It appears that waste can be reduced if retailers follow the optimal policy compared to an easier order-up-to-level policy. When there is willingness to substitute a product for another if the desired product is out of stock, the complexity increases drastically. Basically, one has to take the stock of both products into account. The necessary probabilistic analysis and computational aspects are described in this paper.