Optimal policies for inventory systems with finite capacity and partially observed Markov-modulated demand and supply processes

We analyze a single-item periodic-review inventory system with random yield and finite capacity operating in a random environment. The primary objective is to extend the model of Gallego and Hu (2004) to the more general case when the environment is only partially observable. Although our analysis is specific to inventory systems, it can also be applied to production systems by replacing the fixed capacity supplier with a fixed capacity producer. Using sufficient statistics, we consider single-period, multiple-period and infinite-period problems to show that a state-dependent modified inflated base-stock policy is optimal. Moreover, we show that the multiple-period cost converges to the infinite-period cost as the length of the planning horizon increases.Random yield Fixed capacity Random environment Modified inflated base-stock policy Dynamic programming Sufficient statistics POMDP

Structural Properties of Markov Modulated Revenue Management Problems

Abstract The admission decision is one of the fundamental categories of demand-management decisions. In the dynamic model of the single-resource capacity control problem, the distribution of demand does not explicitly depend on external conditions. However, in reality, demand may depend on the current external environment which represents the prevailing economic, financial, social or other factors that affect customer behavior. We formulate a Markov Decision Process (MDP) to maximize expected revenues over a finite horizon that explicitly models the current environment. We derive some structural results of the optimal admission policy, including the existence of an environment-dependent thresholds and a comparison of threshold levels in different environments. We also present some computational results which illustrate these structural properties. Finally, we extend some of the results to a related dynamic pricing formulation

Spare Parts Management of Aging Capital Products

Spare parts are critical for operations of capital products such as aircraft, refineries, trucks, etc/, which require maintenance regularly. Original Equipment Manufacturers (OEMs) bear the responsibility of undisrupted maintenance service and spare parts flow for their capital products. Due to various factors OEMs lose their spare parts suppliers occasionally and these losses threaten the reliability of their maintenance service and capital products. In this thesis, we consider supply risk in management of spare parts inventory. The thesis consists of two parts: First we develop advance indicators for future supply problems of spare parts and suggest a model utilizing those indicators for inventory control of spare parts. Our results indicate that OEMs can save significantly by utilizing those indicators together with our model in their daily business. Second, we consider secondary markets and their effects on spare parts supply chains of OEMs. Secondary markets are chap supply sources for spare parts needs of OEMs. Therefore effective usage of them yield significant cost savings and boost service rate of OEMs. Furthermore, secondary markets are sources of competition since low prices on those markets attract some customers of OEMs. These two factors are considered from the perspective of spare parts inventory control. In the second part, we conclude that for OEMs it is beneficial to use secondary markets as a supply source as long as they adjust their selling prices accordingly