Learning-based methods for vehicle routing problems - recent advances

Abstract: This talk reviews recent advances in machine learning for combinatorial optimization, with a particular focus on routing problems such as the Traveling Salesman Problem (TSP) and the Capacitated Vehicle Routing Problem (CVRP).

First, I will present a unifying high-level hierarchy of methods. I will then delve deeper into end-to-end reinforcement learning approaches, which have shown strong empirical performance. Finally, I will present our recent work on multi-objective routing over multigraphs, highlighting how learning-based models can handle competing objectives and complex network structures.

machine learningoptimization and controlprobability

Audience: researchers in the discipline

( paper )

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Gothenburg statistics seminar

Series comments: Gothenburg statistics seminar is open to the interested public, everybody is welcome. It usually takes place in MVL14 (http://maps.chalmers.se/#05137ad7-4d34-45e2-9d14-7f970517e2b60, see specific talk). Speakers are asked to prepare material for 35 minutes excluding questions from the audience.

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