A Closed-Form Approximation for Serial Inventory Systems and Its Application to System Design
Manufacturing & Service Operations Management
Optimizing the Supply Chain Configuration for New Products
Management Science
Safety Stock Positioning in Supply Chains with Stochastic Lead Times
Manufacturing & Service Operations Management
Impact of Partial Manufacturing Flexibility on Production Variability
Manufacturing & Service Operations Management
Fuzzy point estimation and its application on fuzzy supply chain analysis
Fuzzy Sets and Systems
Forecast facilitated lot-for-lot ordering in the presence of autocorrelated demand
Computers and Industrial Engineering
Efficient heuristics for inventory placement in acyclic networks
Computers and Operations Research
Strategic Safety Stocks in Supply Chains with Evolving Forecasts
Manufacturing & Service Operations Management
Simultaneous coordination of order quantity and reorder point in a two-stage supply chain
Computers and Operations Research
New model and heuristics for safety stock placement in general acyclic supply chain networks
Computers and Operations Research
Two inventory review policies on supply chain configuration problem
Computers and Industrial Engineering
Inventory placement in acyclic supply chain networks
Operations Research Letters
Manufacturing & Service Operations Management
Supply chain outsourcing risk using an integrated stochastic-fuzzy optimization approach
Information Sciences: an International Journal
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Manufacturing managers face increasing pressure to reduce inventories across the supply chain. However, in complex supply chains, it is not always obvious where to hold safety stock to minimize inventory costs and provide a high level of service to the final customer. In this paper we develop a framework for modeling strategic safety stock in a supply chain that is subject to demand or forecast uncertainty. Key assumptions are that we can model the supply chain as a network, that each stage in the supply chain operates with a periodic-review base-stock policy, that demand is bounded, and that there is a guaranteed service time between every stage and its customers. We develop an optimization algorithm for the placement of strategic safety stock for supply chains that can be modeled as spanning trees. Our assumptions allow us to capture the stochastic nature of the problem and formulate it as a deterministic optimization. As a partial validation of the model, we describe its successful application by product flow teams at Eastman Kodak. We discuss how these flow teams have used the model to reduce finished goods inventory, target cycle time reduction efforts, and determine component inventories. We conclude with a list of needs to enhance the utility of the model.