Mathematics of Operations Research
Mathematics of Operations Research
Critical number policies for inventory models with periodic data
Management Science
Average optimality in dynamic programming with general state space
Mathematics of Operations Research
Lower bounds for multi-echelon stochastic inventory systems
Management Science
Stochastic dynamic programming and the control of queueing systems
Stochastic dynamic programming and the control of queueing systems
Dynamic Programming and Optimal Control
Dynamic Programming and Optimal Control
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
A Capacitated Production-Inventory Model with Periodic Demand
Operations Research
Heuristic Computation of Periodic-Review Base Stock Inventory Policies
Management Science
Probability in the Engineering and Informational Sciences
Safety Stock Positioning in Supply Chains with Stochastic Lead Times
Manufacturing & Service Operations Management
A multi-echelon inventory management framework for stochastic and fuzzy supply chains
Expert Systems with Applications: An International Journal
The benefit of VMI strategies in a stochastic multi-product serial two echelon system
Computers and Operations Research
A Decomposition Approach for a Class of Capacitated Serial Systems
Operations Research
On the Optimal Policy Structure in Serial Inventory Systems with Lost Sales
Operations Research
Managing a Noncooperative Supply Chain with Limited Capacity
Operations Research
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This paper demonstrates optimal policies for capacitated serial multiechelon production/inventory systems. Extending the Clark and Scarf (1960) model to include installations with production capacity limits, we demonstrate that a modified echelon base-stock policy is optimal in a two-stage system when there is a smaller capacity at the downstream facility. This is shown by decomposing the dynamic programming value function into value functions dependent upon individual echelon stock variables. We show that the optimal structure holds for both stationary and nonstationary stochastic customer demand. Finite-horizon and infinite-horizon results are included under discounted-cost and average-cost criteria.