Abstract In this paper we propose a modification to the standard forecasting, periodic order-up-tolevel inventory control approach to dealing with intermittent demand items, when the lead-time length is shorter than the average inter-demand interval. In particular, we develop an approach that relies upon the employment of separate estimates of the interdemand intervals and demand sizes, when de...

purchase or non-purchase of one item or itemset on the purchase or non-purchase of another item or itemset. The research in this paper models for incorporating purchase dependencies in retail multi-item inventory management. One illustrative example has been discussed with data mining in retail sale data. Various types of purchase dependencies including negative dependency have been identified ...

Inventory control of spare parts is essential to many organizations, since excess inventory leads to high holding costs and stock outs can have a great impact on operations performance. This paper proposes a methodology for effective spare parts inventory control, motivated by a case study at a large oil refinery. Different demand modeling techniques and inventory policies are evaluated using r...

We analyze a joint pricing and inventory control problem for a perishable product with a fixed lifetime over a finite horizon. In each period, demand depends on the price of the current period plus an additive random term. Inventories can be intentionally disposed of and those that reach their lifetime have to be disposed of. The objective is to find a joint pricing, ordering, and disposal poli...

We study inventory control for rental operations in a closed-loop supply chain. In such a system (e.g., Netflix), customers create online queues in a service provider’s website to indicate the items that they would like to rent. Leveraging this advance demand information, we propose effective forecast models and formulate a multi-item inventory control problem. We prove that the (L,U) policy is...

To have an efficient control of a huge amount of inventory items, traditional approach is to classify the inventory into different groups. Different inventory control policies can then applied to different groups. The well-known ABC classification is simple-to-understand and easy-to-use. However, ABC analysis is based on only single measurement such as annual dollar usage. It has been recognize...

We consider a stochastic inventory control problem with Markovian capacity and the option of order rejection. We show its optimal policy to be the combination of a capacity-dependent modified base-stock production policy and a capacity-dependent critical-point order acceptance policy. When capacity is stochastically monotone, we show that the policy parameters change over the current capacity l...

Reinforcement Learning (RL) can solve practical sequential decision problems, even when structures of the problems are less understood. However, some sequential decision problems intrinsically have structural parts that are easily to formulate and distinguish from less understood parts. Exploiting this knowledge may help improve performance of RL. This study proposed and investigated an approac...