arXiv Machine Learning July 16, 2026 By Zhengzhong Ricky You, Bo Tang, Haoran Liu, Baichuan Mo

Learned Pairwise Deep Dual-Optimal Inequalities for Stabilizing Column Generation

Read the original on arXiv Machine Learning →

arXiv:2607. 13373v1 Announce Type: cross Abstract: Column generation (CG) is central to many large-scale optimization algorithms, including branch-price-and-cut methods for vehicle routing problems, but unstable dual solutions can substantially slow its convergence.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI

Jun 4

Beyond Objective Equivalence: Constraint Injection for LLM-Based Optimization Modeling on Vehicle Routing Problems

arXiv:2606. 04816v1 Announce Type: new Abstract: Large language models (LLMs) increasingly translate natural-language optimization problems into executable solver code.

By Xizi Luo, Changhong He, Dongdong Geng, Chenggong Shi, Yu Mei

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arXiv Machine Learning

Jun 2

Graph Edit Distance Formulation for the Vehicle Routing Problem: Theory and Analysis

arXiv:2606. 01987v1 Announce Type: cross Abstract: We show that the Vehicle Routing Problem (VRP) can be reformulated as a Graph Edit Distance (GED) maximization problem.

By Adel Dabah

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arXiv AI

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Learning to Reduce Search Space for Generalizable Neural Routing Solver

arXiv:2503. 03137v3 Announce Type: replace Abstract: Constructive neural combinatorial optimization (NCO) offers a promising paradigm for solving vehicle routing problems (VRPs) by directly learning to construct approximate optimal solutions, thereby reducing reliance on expert knowledge for algorithm design.

By Changliang Zhou, Xi Lin, Zhenkun Wang, Qingfu Zhang

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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

Aug 11

DualCert: A Solver for the Traveling Salesman Problem with Constraint-Coupled Learning

arXiv:2608. 09042v1 Announce Type: new Abstract: Large traveling salesman problem (TSP) instances require a solver to allocate limited computation while preserving the validity of its outputs.

By Yancheng Song, Yongzhi Qi, Wei Qi, Zuo-Jun Max Shen

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DualCert: A Solver for the Traveling Salesman Problem with Constraint-Coupled Learning

Large traveling salesman problem (TSP) instances require a solver to allocate limited computation while preserving the validity of its outputs. Existing neural--operations-research (OR) hybrids predict guidance without requiring learned transitions to satisfy constraints discovered during search.

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Beyond Objective Equivalence: Constraint Injection for LLM-Based Optimization Modeling on Vehicle Routing Problems

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