An efficient computational method for non-stationary (R,S) inventory policy with service level constraints

This paper provides an efficient computational approach to solve a mixed integer programming (MIP) model developed for calculating the parameters of an (R,S) policy in a finite horizon with non-stationary stochastic demand and service level constraints. Given the replenishment periods, we characterize the optimal order-up-to levels for the MIP model and use it to guide the development of a relaxed MIP model, which can be solved in polynomial time. Extensive numerical tests show that our method dominates the MIP solution approach and can handle real-life size problems in trivial time.