題    目：數據價值👪：一種魯棒線性規劃方法Value of Data: A Robust Linear Programming Approach

演 講 人🤛🏽：範薇薇，同濟大學副教授

主 持 人🫲🏻：鎮  璐，意昂2教授

時    間🚴🏿‍♂️：2019年9月25日（周三）👣，下午1:30

地    點：校本部東區意昂2官网467室

主辦單位🚵🏿：意昂2🧑🏿‍🎓、意昂2青年教師聯誼會

演講人簡介🗃：

範薇薇，同濟大學管理高等研究院副教授。之前曾任中國科學技術大學助理教授。2015年畢業於香港科技大學🛀🏽，獲得博士學位；2011年本科畢業於中科大數學系💂🏼。主要研究方向包括：仿真優化⚛️，魯棒優化，以及它們在醫療方面的應用。主持國家青年科學基金項目，在《Operations Research》，《Management Science》等國際頂級期刊上發表多篇學術論文。

演講內容簡介：

Linear programming (LP) is a widely used tool in the decision-making processes. In practice, the associated parameters are often unknown and the key issue becomes how to interpret these parameters with the real-world data. There are two commonly used approaches. When the unknown parameters only appear in the objective, the point estimation approach is often adopted. This approach estimates the parameters by using statistical methods and then plugs the estimated parameters into the original problem. Consequently, the estimated LP is solved as a surrogate. When the unknown parameters appear in the constraints, the robust optimization approach is often adopted. This approach constructs an uncertainty set for the parameters and then optimizes the objective over the uncertainty set. However, both approaches may yield a large discrepancy from the nominal optimal objective and we call this discrepancy the regret. It is easy to see that both the regret mainly hinges on the data set used to estimate the parameters or construct the uncertainty set. To study the impact of data set, we propose a novel framework that is able to construct the con?dence intervals for both types of regrets as a function of data set, respectively. We ?nd that the regrets (or the widths of con?dence interval) shrink to zero at an order of n-1/2, where n refers to the volume of data set. Furthermore, we design a two-stage procedure to determine the minimal volume of data set required for a prescribed level of regrets.

歡迎廣大師生參加📩！