Convergence Rates of Simulation with Covariates

Speaker: Siyang Gao，City University of Hong Kong

Time:  10:00AM  Oct.12 2020

ZOOM: 672 188 81887 Password:  660611

Abstract:

We consider a recently proposed simulation-based decision-making framework, called simulation with covariates. In this framework, simulation experiments are not performed after the target problem is set up with all the input parameters (known as the covariates, side information or auxiliary information in the literature); instead, they are performed before that with all the possible parameters that might come up in the target problem. Then, these computational results are directly used in real time for system evaluation or system optimization when the input parameters of the target problem are known. In this research, we will follow this framework and use stochastic kriging (SK) to model the system performance from the covariate space. Two measures, namely the maximal integrated mean squared error (IMSE) and integrated probability of false selection (IPFS), are proposed to evaluate the prediction errors for system evaluation and system optimization respectively. We establish the convergence rates of these two measures with the number of covariate points. They quantify the magnitude of prediction errors for the online application after a certain period of time is spent for offline simulation.

Speaker’s Bio:

Siyang Gao received the B.S. degree in Mathematics from Peking University, Beijing, China, in 2009, and the Ph.D. degree in Industrial Engineering from University of Wisconsin-Madison, Madison, WI, in 2014. Dr. Gao is an Associate Professor with the Department of Systems Engineering and Engineering Management, City University of Hong Kong. His research is devoted to simulation optimization, large-scale optimization and their applications in healthcare management. His work has appeared in Operations Research, IEEE Transactions on Automatic Control, Automatica, etc. He is a recipient of the Best Conference Paper Award at the IEEE Conference on Automation Science and Engineering in 2019, Best Paper Award at the International Conference on Logistics and Maritime Systems in 2019, and the Best Young Faculty Paper Award at the International Research Conference on Systems Engineering and Management Science in 2018. Dr. Gao is a member of the Institute for Operations Research and the Management Sciences (INFORMS) and Institute of Electrical and Electronics Engineers (IEEE).