IE Decision Systems Engineering Seminar Spring 2018: Reducing simulation model risk via input model averaging
Presented by Barry L. Nelson, Walter P. Murphy Professor, Northwestern University. Nelson's research focus is on the design and analysis of computer simulation experiments on models of discrete-event, stochastic systems, including methodology for simulation optimization, quantifying and reducing model risk, variance reduction, output analysis, metamodeling and multivariate input modeling.
In this seminar, Nelson will show that frequentist model averaging can be a provably effective way to create input models that better represent the true, unknown input distributions, thereby reducing model risk. Input model averaging builds from standard input modeling practice and requires no change in how the simulation is executed nor any follow-up experiments.
Friday, April 13, 2018, Noon
Brickyard (BYENG) 209, Tempe campus
Information and flier:
Sponsor: School of Computing, Informatics, and Decision Systems Engineering in the Ira A. Fulton Schools of Engineering at Arizona State University.
Host: Giulia Pedrielli, Senior Sustainability Scientist