뉴스 및 공지사항
- 관리자
- 2024.06.05
- 560
[세미나] [ISE/GSDS Seminar] June 13, 16:00 / B105 in E-2 Building / Professor Eunhye Song, Georgia Tech
The ISE/GSDS department will be hosting the following seminar:
- Date/Time: Thursday, June 13, 2024, 16:00-17:00
- Location : B105, E2 Building
- Presenter: Professor Eunhye Song, H. Milton Steward School of Industrial & Systems Engineering, Gerogia Tech
- Title: Optimizing the input data collection for ranking and selection
- Abstract: We investigate a Bayesian ranking and selection (R&S) problem under input uncertainty when all solutions share a collection of independent input models. These Bayesian input models are updated as more data is collected from multiple independent sources ultimately converging to the data-generating distributions. Our goal is to design a sequential sampling algorithm that identifies the true optimum under the data-generating distributions most efficiently given a data collection budget. Two types of data collections are considered: input data acquisition from each source and simulation sampling for a solution at a particular set of input models. We propose the most probable best (MPB) as a Bayesian estimator of the optimum and characterize its probabilistic convergence rate to the optimum focusing on the case when there is a finite set of candidates for the true input distributions. We derive the optimal asymptotic static sampling ratios for the input data collection and simulation by maximizing the rate function. Based on this analysis, a sequential sampling algorithm is proposed, which is further bolstered by combining the kernel ridge regression to improve the mean prediction at the solution-input model pairs. We benchmark our algorithm against a state-of-the-art method that considers the same R&S problem.
-Bio: Eunhye Song is a Coca-Cola Foundation Early Career Professor and Assistant Professor at the H. Milton Stewart School of Industrial and Systems Engineering. She earned her PhD in Industrial Engineering and Management Sciences from Northwestern University in 2017. She was a Harold and Inge Marcus Early Career Assistant Professor in Industrial and Manufacturing Engineering at Penn State University from 2017 to 2022 before joining Georgia Tech in July 2022. Her core research area is theoretical and algorithmic analysis of stochastic simulation with a focus on robust decision-making with data-driven simulation. She is a recipient of the US National Science Foundation CAREER Award and won an Honorable Mention in the 2020 INFORMS JFIG Paper Competition. She is an active member of the INFORMS Simulation Society and has served on various conference organizing/award committees since 2017.
- The seminar will be given in English.