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...

Inventory control in a supply chain is crucial for companies desiring to satisfy their customers demands as well as controlling costs. This paper examines specifically supply planning under uncertainties in MRP environments. Models from literature that deals with random demand or lead time uncertainties are described and commented. Promising research areas emerge from this survey. It appears th...

The development of control-oriented decision policies for inventory management in supply chains has received considerable interest in recent years, and demand modeling to supply forecasts for these policies is an important component of an effective solution to this problem. Drawing from the problem of controlrelevant identification, we present an approach for demand modeling based on data that ...

We consider a stochastic inventory control problem in which a buyer makes procurement decisions while facing periodic random demand and two supply sources, namely, a long-term contract supplier and a spot market. The contract between the buyer and the supplier partially shields the latter from the vicissitudes of the spot market, in that the price paid by the buyer to the supplier is only parti...

This paper considers a concurrent pricing and inventory control problem in a stochastic and periodic review setting. Demand in a period is random and depends on the posted price. Other than holding and backlogging costs, the system incurs stock-replenishment costs that consist of both variable and fixed components. At the beginning of each period, a simultaneous decision has to be made on stock...

Bid-prices are becoming an increasingly popular method for controlling the sale of inventory in revenue management applications. In this form of control, threshold—or ‘‘bid’’—prices are set for the resources or units of inventory (seats on flight legs, hotel rooms on specific dates, etc.) and a product (a seat in a fare class on an itinerary or room for a sequence of dates) is sold only if the ...

ARTICLE INFO An agricultural tractor seat with passive suspension system gives a number of advantages when compared with currently available seat designs. Analysis on the vibration of tractor seat suspension system by using the different types of the suspension system is carried out for the different types of operation and analyze the suspension system separately to find out the reduction in th...