activity
20202022
most citedLearning to Solve Vehicle Routing Problems with Time Windows through Joint Attention

16 citations · 20 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG20224 cited

Large Neighborhood Search based on Neural Construction Heuristics

Jonas K. Falkner, Daniela Thyssens, Lars Schmidt-Thieme

We propose a Large Neighborhood Search (LNS) approach utilizing a learned construction heuristic based on neural networks as repair operator to solve the vehicle routing problem wi…

cs.LG2022

Supervised Permutation Invariant Networks for Solving the CVRP with Bounded Fleet Size

Daniela Thyssens, Jonas Falkner, Lars Schmidt-Thieme

Learning to solve combinatorial optimization problems, such as the vehicle routing problem, offers great computational advantages over classical operations research solvers and heu…

cs.LG2021

Improving Hyperparameter Optimization by Planning Ahead

Hadi S. Jomaa, Jonas Falkner, Lars Schmidt-Thieme

Hyperparameter optimization (HPO) is generally treated as a bi-level optimization problem that involves fitting a (probabilistic) surrogate model to a set of observed hyperparamete…

cs.LG2021

RP-DQN: An application of Q-Learning to Vehicle Routing Problems

Ahmad Bdeir, Simon Boeder, Tim Dernedde +3

In this paper we present a new approach to tackle complex routing problems with an improved state representation that utilizes the model complexity better than previous methods. We…

cs.LG202016 cited

Learning to Solve Vehicle Routing Problems with Time Windows through Joint Attention

Jonas K. Falkner, Lars Schmidt-Thieme

Many real-world vehicle routing problems involve rich sets of constraints with respect to the capacities of the vehicles, time windows for customers etc. While in recent years firs…