TU Delft, The Netherlands
June 05, 2024, 11:00, Room GC B1 10 (click here for the map)
In Inverse Optimization problems, a learning agent aims to learn how to mimic the behavior of an expert agent, which given an exogenous signal, returns an action. The underlying assumption is that in order to compute its action, the expert agent solves an optimization problem parametric in the exogenous signal. Therefore, given examples of exogenous signals and corresponding expert actions, the goal of the learner is to learn the cost function being optimized by the expert. In this talk, we will present fundamental concepts of Inverse Optimization and novel results, as well as applications to static and dynamic routing problems for the 2021 Amazon Last Mile Routing Research Challenge and the EURO Meets NeurIPS 2022 Vehicle Routing Competition.
Pedro is a PhD student at the Mechanical Engineering department at the Technical University of Delft, The Netherlands.