Power approximation for computing (s,S) policies using service level
Management Science
Simple solution procedures for a class of two-echelon inventory problems
Operations Research
WSC '94 Proceedings of the 26th conference on Winter simulation
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Serial Production/Distribution Systems Under Service Constraints
Manufacturing & Service Operations Management
Heuristic Methods for Centralized Control of One-Warehouse, N-Retailer Inventory Systems
Manufacturing & Service Operations Management
Safety Stock Positioning in Supply Chains with Stochastic Lead Times
Manufacturing & Service Operations Management
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We present a simulation-regression based method for obtaining inventory policies for a two-echelon distribution system with service level constraints. Our motivation comes from a wholesale distributor in the consumer products industry with thousands of products that have different cost, demand, and lead time characteristics. We need to obtain good inventory policies quickly so that supply chain managers can run and analyze multiple scenarios effectively in reasonable amount of time. While simulation-based optimization approaches can be used, the time required to solve the inventory problem for a large number of products is prohibitive. On the other hand, available quick approximations are not guaranteed to provide satisfactory solutions. Our approach involves sampling the universe of products with different problem parameters, obtaining their optimal inventory policies via simulation-based optimization and then using regression methods to characterize the inventory policy for similar products. We show that our method obtains near-optimal policies and is quite robust.