arXiv AI
EDISCO: Equivariant DIScrete Diffusion for Euclidean Combinatorial Optimization
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GeoRouteNet: A Geometry-Aware Non-Autoregressive Neural Solver for the Euclidean Traveling Salesman Problem
arXiv:2606. 22776v2 Announce Type: replace-cross Abstract: Non-autoregressive neural solvers amortize computation across traveling salesman problem (TSP) instances, but models trained on random Euclidean instances can degrade when the number or spatial distribution of nodes changes.
arXiv AI
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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.
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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.
arXiv AI
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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.
arXiv Machine Learning
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The Optimal Sampler for Diverse TSP Solutions: Characterization, Limits, and Learning
arXiv:2610.28994v1 Announce Type: cross Abstract: We address the Diverse Traveling Salesman Problem (D-TSP) that seeks a set of $k$ distinct TSP tours. Each selected tour must not exceed a prescribed...
arXiv Machine Learning
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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.