Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Computers and Operations Research
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The management of inventories of perishable products with a short maximal shelf life takes a good issuing policy next to a good ordering policy. Ordering policies of non-perishables are well studied in literature and implemented in Automated Store Ordering (ASO) systems and Computer Assisted Ordering (CAO) systems. These ordering policies are stock-level dependent and do not take the product ages into account. As a consequence when applied to perishable products they do not anticipate expected future outdating of products and thus result in unnecessary outdating and shortages. Improved ordering policies are proposed in the literature but hardly implemented in ASO and CAO systems as these are designed for the management of non-perishables. Without changing the order policies of such systems one may reduce outdating and shortages by issuing the products in a sophisticated way. We present therefore a stochastic model that is solved by stochastic dynamic programming.