Inventory service-level measures: convexity and approximation
Management Science
On properties of stochastic inventory systems
Management Science
Installation vs. echelon stock policies for multilevel inventory control
Management Science
A multiechelon inventory model with fixed replenishment intervals
Management Science
Managing Supply Chain Demand Variability with Scheduled Ordering Policies
Management Science
Near-Optimal Echelon-Stock (R, Nq) Policies in Multistage Serial Systems
Operations Research
Optimal Policies for Multi-Echelon Inventory Problems with Batch Ordering
Operations Research
Properties of the Periodic Review (R, T) Inventory Control Policy for Stationary, Stochastic Demand
Manufacturing & Service Operations Management
Optimal Control of Serial Inventory Systems with Fixed Replenishment Intervals
Operations Research
Serial Supply Chains with Economies of Scale: Bounds and Approximations
Operations Research
Note: A Simple Heuristic for Serial Inventory Systems with Fixed Order Costs
Operations Research
Echelon-stock (R,nT) control in two-stage serial stochastic inventory systems
Operations Research Letters
Improving Supply Chain Performance: Real-Time Demand Information and Flexible Deliveries
Manufacturing & Service Operations Management
A simple heuristic for echelon (r,nQ, T) policies in serial supply chains
Operations Research Letters
Lower Bounds and Heuristics for Supply Chain Stock Allocation
Operations Research
Technical Note---On Optimal Policies for Inventory Systems with Batch Ordering
Operations Research
Joint shipment consolidation and inventory decisions in a two-stage distribution system
Computers and Industrial Engineering
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This paper studies a periodic-review, serial inventory system in which echelon (r, nQ, T) policies are implemented. Under such a policy, each stage reviews its inventory in every T period and orders according to an echelon (r, nQ) policy. Two types of fixed costs are considered: one is associated with each order batch Q, and the other is incurred for each inventory review. The objective is to find the policy parameters such that the average total cost per period is minimized. This paper provides a method for obtaining heuristic and optimal policy parameters. The heuristic is based on minimizing lower and upper bounds on the total cost function. These total cost bounds, which are separable functions of the policy parameters, are obtained in two steps: First, we decompose the total cost into costs associated with each stage, which include a penalty cost for holding inadequate stock. Second, we construct lower and upper bounds for the penalty cost by regulating downstream policy parameters. To find the optimal solution, we further construct cost bounds for each echelon (a subsystem that includes a stage and all of its downstream stages) by regulating holding and backorder cost parameters. The echelon lower-bound cost functions, as well as the stage cost bounds, generate bounds for the optimal solution. In a numerical study, we find that the heuristic is near optimal when the ratio of the fixed cost to the holding cost at the most downstream stage is large. We also find that changing the optimal batch sizes may not affect the optimal reorder intervals or, equivalently, the delivery schedules under some conditions.