Safety stock optimization in multi-stage inventory systems

Determining appropriate safety stocks in stochastic multi-stage production/distribution systems is a very difficult task. Approaches for optimal determination of safety stocks regarding cost objectives and service level restrictions which are suitable for practical applications can only be found for a very limited class of multi-stage inventory problems like problems of strictly serial structure or special two-stage production/distribution systems. In this paper a procedure for determining the optimal size and distribution of safety stocks in a general serial or divergent production/distribution process ruled by a base-stock control policy is presented. This approach especially allows for taking into account the impact of end-item demand correlation on distribution and size of safety stocks by using risk-pooling effects in divergent systems. A powerful dynamic programming algorithm for solving the safety stock optimization problem is developed, and impacts of problem parameter variations on the optimal solution are discussed.