Manufacturers make production decisions and carry inventory to satisfy uncertain demand. When holding and shortage costs are high, carrying inventory could be even more expensive for a capacitated production system. Recent developments in information technology and sales strategies enabled firms to acquire, collect, or induce advance demand information. We address a periodic-review, stochastic,...

We consider the joint pricing and inventory control problem for a single product with a finite horizon and periodic review. The demand distribution in each period is determined by an exogenous Markov chain. Pricing and ordering decisions are made at the beginning of each period and all shortages are backlogged. The surplus costs as well as fixed and variable costs are state dependent. We show t...

Solving Robust Inventory Problems In this work we consider setting the optimal inventory control policies for a single buffer when demand is uncertain, in a robust framework. Unlike traditional inventory models we do not assume that the demand is random with a known distribution. Instead, demand can take values from a given uncertainty set. Our objective is to find the policy that minimize the ...

The common belief is that using Reinforcement Learning methods (RL) with bootstrapping gives better results than without. However, inclusion of bootstrapping increases the complexity of the RL implementation and requires significant effort. This study investigates whether inclusion of bootstrapping is worth the effort when applying RL to inventory problems. Specifically, we investigate bootstra...

We consider the periodic review inventory control problem in which the purchasing cost of the product changes, in a Markovian fashion, from one period to the next. After establishing (with and without the non-speculation assumption) that an order upto policy is optimal, we develop an efficient recursive solution procedure to compute the optimal levels. In addition, we propose a measure for the ...

A significant amount of work has investigated inventory control problems associated with fresh produce. Much of this work has considered deteriorating inventory control with many models having been proposed for the various situations that exist. However, no researchers have specifically studied fresh produce which has its own special characteristics. Most research categorise fresh produce into ...

Traditional computerised inventory control systems usually rely on exponential smoothing to forecast the demand for fast moving inventories. Practices in relation to slow moving inventories are more varied, but the Croston method is often used. It is an adaptation of exponential smoothing that 1) incorporates a Bernoulli process to capture the sporadic nature of demand and 2) allows the average...

This paper would firstly introduce the Single-Period Inventory Model, a basic method of inventory control. By analyzing Newsvendor Problem which is simplified situation storing inventories, this discover using normal distribution analysis to solve problem. Then, promote adoption into realistic problems and discuss its utility. Secondly, topic expanded Multi-Period System. system focus on more s...