Kevin Tierney, Bielefeld University

Abstract

Deep reinforcement learning (DRL) offers a way to automatically learn heuristics to solve routing problems. Over the past years, these techniques have rapidly improved in terms of the quality of solutions they find, although they have not yet overtaken state-of-the-art "traditional" OR heuristics. I provide an overview of how to solve routing problems using DRL, starting from constructing solutions, and continuing on to advanced search techniques. This talk discusses both the limitations and opportunities of DRL to try to determine whether learning to optimize is just the latest trend or a future technology.

[Video]