題 目：Managing with Incomplete Inventory Information
主講人：Sethi Suresh Pal. (加拿大皇家科學院院士、杰出教授、博士)
時 間：2013年8月26日(星期一)15點
地 點：主樓418會議室
主講人簡介：
Suresh P. Sethi任教于德克薩斯大學達拉斯分校，現為加拿大皇家科學院院士，Charles & Nancy Davidson運作管理的杰出教授，智能供應網絡中心主任(the Center for Intelligent Supply Networks)。Sethi教授在運作管理、營銷、工業工程、最優控制等領域做出了杰出貢獻，最為人熟知是Sethi advertising model、DNSS Points以及有關最優控制的教科書，如Optimal Control Theory: Applications to Management Science and Economics。Sethi教授在國際主流期刊上發表學術論文264篇，其中Management Science 11篇, Operations Research 17篇, Production and Operations Management 15篇, Manufacturing & Service Operations Management 5篇。Sethi教授現為Production and Operations Management協會主席，同時擔任Production and Operations Management期刊（UT Dallas 24種頂級期刊之一）的Department Editor，SIAM Journal on Control and Optimization的責任編輯，Automatica的副主編。現擔任Management Science、Operations Research(OR)、IIE Transactions(IIE) 、Manufacturing & Service Operations Management等多種權威期刊的審稿專家。
內容簡介：
A critical assumption in the vast literature on inventory management has been that the current level of inventory is known to the decision maker. Some of the most celebrated results such as optimality of base-stock have been obtained under this assumption. Yet it is often the case in practice that the decision makers have incomplete or partial information about their inventory levels. The reasons for this are many: Inventory records or cash register information differ from actual inventory because of a variety of factors including transaction errors, theft, spoilage, misplacement, unobserved lost demands, and information delays. As a result, what are usually observed are some events or surrogate measures, called signals, related to the inventory level. At best, these relationships may provide only the distribution of current inventory levels. In the best case, therefore, the relevant state in the inventory control problems is not the current inventory level, but rather its distribution given the observed signals. Thus, the analysis for finding optimal production or ordering policies takes place generally in the space of probability distributions. The purpose of this talk is to review recent developments in the analysis of inventory management problems with incomplete information.
