This paper studies supply chain demand variability in a model with one supplier and N retailers that face stochastic demand. Retailers implement scheduled ordering policies: Orders occur at fixed intervals and are equal to some multiple of a fixed batch size. A method is presented that exactly evaluates costs. Previous research demonstrates that the supplier’s demand variance declines as the re...

The popular models for repairable item inventory, both in the literature as well as practical applications, assume that the demands for items are independent of the number of working systems. However this assumption can introduce a serious underestimation of availability when the number of working systems is small, the failure rate is high or the repair time is long. In this paper, we study a m...

We consider combined inventory control and throughput time reduction in multi-echelon, multiindenture spare part networks for system upkeep of capital goods. We construct a model in which standard throughput times (TPT) for repair and transportation can be reduced at additional costs. We first estimate the marginal impact of TPT reduction on the system availability. Next, we develop an optimiza...

In this paper, we describe a simulation-based inventory management tool developed for the IBM Enterprise Server Group. Through the Web interface of the tool, an inventory manager is able to visualize Days of Supply (DOS) levels – current and projected, and to carry out what-if scenario analysis to identify potential opportunities for improvement. The highly complicated server manufacturing envi...

We consider the classic N -stage serial supply systems with linear costs and stationary random demands. There are deterministic transportation leadtimes between stages, and unsatisfied demands are backlogged. The optimal inventory policy for this system is known to be an echelon base-stock policy, which can be computed through minimizing N nested convex functions recursively. To identify the ke...

We consider an assembly system with multiple stages, multiple items, and multiple customer classes. The system consists of m production facilities, each producing a different item. Items are produced in variable batch sizes, one batch at a time, with exponentially distributed batch production times. Demand from each class takes place continuously over time according to a compound Poisson proces...

Almost all multi-echelon inventory models assume that demand not satis ed immediately can be backordered. In some situations this assumption is not realistic. For example, it may be more representative to model stockouts as lost sales when the retailers are in a competitive market and customers can easily turn to another rm when purchasing the good. Assuming lost sales at the retailers, we cons...

We have used Reinforcement Learning together with Monte Carlo simulation to solve a multi-period production planning problem in a two-stage hybrid manufacturing process (a combination of build-to-plan with build-to-order) with a capacity constraint. Our model minimizes inventory and penalty costs while considering real-world complexities such as different component types sharing the same manufa...