Service Level Constrained Inventory Systems
Motivated by the importance of service quality in today's customer business environment, we consider two periodic review stochastic inventory models with probabilistic service level guarantees for restricting stockout probabilities: (i) the classical inventory control model with backlogging and (ii) the remanufacturing inventory control model with random product returns. We assume that demands are stochastic nonstationary, evolving and correlated over time. We establish the optimality of generalized base stock policies, and propose new 2 approximation algorithms for both models. The core concept developed in this paper is called the delayed forced holding and production cost, which is proven effective in dealing with service level constrained inventory systems. Our extensive computational experiments show that the proposed algorithms on average perform within 2% error of optimality.