Research on integrated optimization problem in a multi-product supply chain based on Markov decision processes

The paper considers the application of a modified policy iterative algorithm for the integrated optimization problem of the location and inventory decisions of a distribution center (DC), constrained by given customer service levels in a multi-product multi-echelon supply chain, which is formulated as an integrated optimization model based on a Markov process. The problem is motivated by a real situation faced by a Chinese food company. In this problem, the DC receives different products from several suppliers, and delivers them to retailers with limited capacity vehicles, making sure that every retailer can achieve their required customer service levels. The problem is to determine the location, order policy and delivery policy of the DC. The objective is to minimize the expected total long-term cost with the satisfaction of desired customer service levels. The theoretical analysis and computational results show that the proposed integrated model is much more practical than separated ones because of the consideration of the inherent relationships between facility costs, inventory costs, transportation costs, and customer service levels. It also suggests effective methods and solutions for a variety of integrated optimization of complex logistics system.