most citedAttention, Filling in The Gaps for Generalization in Routing Problems

2 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023

Routing Arena: A Benchmark Suite for Neural Routing Solvers

Daniela Thyssens, Tim Dernedde, Jonas K. Falkner +1

Neural Combinatorial Optimization has been researched actively in the last eight years. Even though many of the proposed Machine Learning based approaches are compared on the same…

cs.LG20231 cited

Too Big, so Fail? -- Enabling Neural Construction Methods to Solve Large-Scale Routing Problems

Jonas K. Falkner, Lars Schmidt-Thieme

In recent years new deep learning approaches to solve combinatorial optimization problems, in particular NP-hard Vehicle Routing Problems (VRP), have been proposed. The most impact…

cs.LG2023

Neural Capacitated Clustering

Jonas K. Falkner, Lars Schmidt-Thieme

Recent work on deep clustering has found new promising methods also for constrained clustering problems. Their typically pairwise constraints often can be used to guide the partiti…

cs.LG20222 cited

Attention, Filling in The Gaps for Generalization in Routing Problems

Ahmad Bdeir, Jonas K. Falkner, Lars Schmidt-Thieme

Machine Learning (ML) methods have become a useful tool for tackling vehicle routing problems, either in combination with popular heuristics or as standalone models. However, curre…

cs.LG20222 cited

Solving the Traveling Salesperson Problem with Precedence Constraints by Deep Reinforcement Learning

Christian Löwens, Inaam Ashraf, Alexander Gembus +3

This work presents solutions to the Traveling Salesperson Problem with precedence constraints (TSPPC) using Deep Reinforcement Learning (DRL) by adapting recent approaches that wor…