威尼斯欢乐娱人城v3676(China)APP官网-BinG百科

ABSTRACT: We study joint inventory-price control in which a firm chooses among a finite number of prices to influence the demand to be realized; also, the firm's ordering activities may incur fixed setup costs. While intending to settle down on an optimal (s,S,p) inventory-price policy all catering to the long-run average criterion, the firm knows little, not even any form presumably taken by the demand-price relationship such as multiplicative or additive, about the demand distributions that it is to face under various prices. We propose an adaptive policy in which exploration involving all-price sweeps and exploitation relying on best policies catered to empirical demand distributions are carried out intermittently, with the latter activity becoming ever more pervasive over time. When its learning-doing schedule is finely tuned, this policy can achieve an O(T^{2/3}) regret guarantee. Other policy ideas have been considered as well. One that applies the UCB principle to the determination of policies to be adopted in ever lengthier intervals can achieve an O(T^{1/2}) regret guarantee for the special case without fixed setup costs. Our numerical analysis reveals the merits of other policies.

报告人：Prof. Jian Yang （美国罗格斯大学威尼斯欢乐娱人城v3676）

报告人简介：Dr. Jian Yang obtained his Ph.D. in Management Science from the University of Texas at Austin.  After working for the Department of Mechanical and Industrial Engineering at New Jersey Institute of Technology, he is now a professor at the Department of Management Science and Information Systems, Rutgers Business School, Rutgers University.  Dr. Yang’s research interests are in combinatorial optimization, logistics, production and inventory control, dynamic pricing, and game theory.  At the present he is particularly interested in the role played by risk and ambiguity in dynamic inventory-price control and game-theoretical settings.