arXiv Machine Learning July 7, 2026 By Marek Eli\'a\v{s}, Fabrizio Grandoni, Adam Polak, Eleonora Vercesi

TSP with Predictions: Heatmap to Tour with Provable Guarantees

Read the original on arXiv Machine Learning →

arXiv:2607. 03791v1 Announce Type: cross Abstract: The Traveling Salesperson Problem (TSP) has long served as a benchmark for evaluating the strength of optimization techniques in the classical theory of algorithms.

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benchmarks

arXiv AI

Jul 28

Understanding Human-like Solutions in Combinatorial Optimization via Learning and Search

arXiv:2607. 23854v1 Announce Type: new Abstract: Humans often find good solutions to combinatorial optimization problems that are computationally hard even for advanced computer algorithms.

By Haijiang Yan, Jian-Qiao Zhu, Liqiang Huang, Ming Meng

reinforcement-learning fine-tuning

arXiv AI

Jun 9

Leveraging Structural Constraints for Diffusion-based Neural TSP Solvers

arXiv:2606. 09343v1 Announce Type: new Abstract: Neural combinatorial optimization has recently achieved strong results on the Euclidean Traveling Salesman Problem (TSP) using generative models such as diffusion and consistency models.

By Micka\"el Basson (CRIStAL, Scool), Philippe Preux (CRIStAL, Scool)

diffusion

arXiv AI

Jun 9

IDEQ -- Improving Diffusion Models for the Traveling Salesman Problem (TSP) by Leveraging the Structure of the Solution Space

arXiv:2412. 13858v2 Announce Type: replace Abstract: We investigate diffusion models to solve the Traveling Salesman Problem.

By Mickael Basson, Philippe Preux

diffusion benchmarks

arXiv Machine Learning

Jul 22

Graph Neural Network-based Algorithm Selection for the Traveling Salesman Problem: A Systematic Study of Cost and Rank Losses under Distinct Budget Regimes

arXiv:2607. 18632v1 Announce Type: new Abstract: Automated Algorithm Selection (AS) aims to improve problem-solving performance by selecting, for each problem instance, the most suitable algorithm from a predefined portfolio.

By Zhaoxuan Li, Jiale Yang, Yifei Lu, Mustafa Misir

arXiv AI

Jul 15

Connected by Construction: Learning Tractable Near-Tour Marginals for Traveling Salesman Problems

arXiv:2607. 12127v1 Announce Type: new Abstract: Learning-based methods for the traveling salesman problem (TSP) are often evaluated through the tours produced after decoding or search, but the learned object itself frequently lives in a surrogate space such as heatmaps, assignments, construction policies, or search-guidance scores.

By Ke Sun, Xinyuan Zhang, Xinwu Qian

arXiv Machine Learning

Jun 18

AGDN: Learning to Solve Traveling Salesman Problem with Anisotropic Graph Diffusion Network

arXiv:2606. 19185v1 Announce Type: new Abstract: The Traveling Salesman Problem (TSP) is a cornerstone of combinatorial optimization and arises in many practical scenarios.

By Bolin Shen, Ziwei Huang, Zhiguang Cao, Yushun Dong

diffusion

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Understanding Human-like Solutions in Combinatorial Optimization via Learning and Search

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IDEQ -- Improving Diffusion Models for the Traveling Salesman Problem (TSP) by Leveraging the Structure of the Solution Space

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