Heuristic inventory policies for a hybrid manufacturing/remanufacturing system with product substitution

We consider inventory control for an infinite-horizon hybrid manufacturing/remanufacturing system with product substitution under stochastic demand and returns. Remanufactured and manufactured products are considered as different products having different costs and selling prices as well as separate demand streams. Remanufactured products have a higher stock out risk than manufactured products because the remanufacturing capacity is dependent on available returns for remanufacture. One way to cope with this stock-out risk is to use a downward substitution strategy, under which a manufactured product (i.e. higher value item) substitutes for a remanufactured product (i.e. lower value item) in case the latter runs out of stock, This problem can be formulated as a Markov Decision Process in order to determine the optimal manufacturing and remanufacturing decisions under product substitution. However, the optimal policy has a complicated structure. Based on characterization of the optimal policies, we propose intuitive heuristic policies that are easy to implement in practice. Then, we develop a heuristic search technique to determine the parameter values for these policies in an efficient way. We evaluate the performance of the proposed heuristic policies compared to the optimal inventory policy through a real case study involving a spare part manufacturer.