|
The University of Toronto Operations Research Group (UTORG) is hosting a lunch talk by Rafiq Mahmood. The talk is entitled “Multiple Observations and Goodness of Fit in Generalized Inverse Optimization”. Lunch and coffee will be provided. Hope to see you there! When: Wednesday, July 4th @ 12:00pm – 1:00pm Where: MB101 Bio-sketch: Rafid Mahmood received his B.A.Sc. and M.A.Sc. degrees in Electrical and Computer Engineering from the University of Toronto in 2013 and 2015 respectively. He is pursuing his Ph.D. degree in Mechanical & Industrial Engineering at the University of Toronto. His research interests focus on the intersection of information theory, optimization, and deep learning for applications in multimedia streaming, health care, and sports analytics. |
|
| Abstract: Inverse optimization is the practice of using observed decisions to model a latent optimization problem. This work develops a generalized inverse linear optimization framework for imputing objective function parameters given a data set containing both feasible and infeasible points. We devise assumption-free, exact solution methods to solve the inverse problem; under mild assumptions, we show that these methods can be made more efficient. We extend a goodness-of-fit metric previously introduced for the problem with a single observed decision to this new setting, proving and numerically illustrating several important properties. |