Travelling Salesman Problem

Learning the Travelling Salesperson Problem Requires Rethinking Generalization
We study zero-shot generalization to large-scale instances in neural network-driven solvers for the Travelling Salesman Problem: what architectures, inductive biases and learning paradigms enable better generalization? (Invited submission to the Constraints Journal)
Chaitanya K. Joshi, Quentin Cappart, Louis-Martin Rousseau, Thomas Laurent
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Learning the Travelling Salesperson Problem Requires Rethinking Generalization
Learning TSP Requires Rethinking Generalization
We study zero-shot generalization to large-scale instances in neural network-driven solvers for the Travelling Salesman Problem: what architectures, inductive biases and learning paradigms enable better generalization? (CP 2021)
Chaitanya K. Joshi, Quentin Cappart, Louis-Martin Rousseau, Thomas Laurent
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Learning TSP Requires Rethinking Generalization
On Learning Paradigms for the Travelling Salesman Problem
How do learning paradigms impact zero-shot generalization to large-scale instances in learning-driven TSP solvers? (NeurIPS 2019 Workshop)
Chaitanya K. Joshi, Thomas Laurent, Xavier Bresson
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On Learning Paradigms for the Travelling Salesman Problem
An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem
Deep Graph ConvNets paired with parallelized graph search can learn TSP up to few hundred cities, but fall short of classical solvers.
Chaitanya K. Joshi, Thomas Laurent, Xavier Bresson
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An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem
Graph Convolutional Neural Networks for the Travelling Salesman Problem
Combinatorial optimization problems, also called NP-hard problems, are practical constraint satisfaction problems that are impossible …
Chaitanya K. Joshi
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Graph Convolutional Neural Networks for the Travelling Salesman Problem