{"total":60,"rows":[{"id":"2402.01145","title":"ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution","created":"2024-02-02","cited_by_count":276,"area":null},{"id":"2310.07985","title":"Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization","created":"2023-10-12","cited_by_count":142,"area":null},{"id":"2210.04123","title":"DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems","created":"2022-10-08","cited_by_count":129,"area":null},{"id":"2205.13209","title":"Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization","created":"2022-05-26","cited_by_count":119,"area":null},{"id":"2310.18264","title":"Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt","created":"2023-10-27","cited_by_count":81,"area":null},{"id":"2309.14032","title":"DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization","created":"2023-09-25","cited_by_count":78,"area":null},{"id":"2306.17100","title":"RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark","created":"2023-06-29","cited_by_count":71,"area":null},{"id":"2305.19587","title":"Towards Omni-generalizable Neural Methods for Vehicle Routing Problems","created":"2023-05-31","cited_by_count":69,"area":null},{"id":"2203.15386","title":"Pareto Set Learning for Neural Multi-objective Combinatorial Optimization","created":"2022-03-29","cited_by_count":56,"area":null},{"id":"2311.15249","title":"Algorithm Evolution Using Large Language Model","created":"2023-11-26","cited_by_count":53,"area":null},{"id":"2207.05984","title":"Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation","created":"2022-07-13","cited_by_count":32,"area":null},{"id":"2410.16309","title":"In-the-loop Hyper-Parameter Optimization for LLM-Based Automated Design of Heuristics","created":"2024-10-07","cited_by_count":28,"area":null},{"id":"2404.11677","title":"Cross-Problem Learning for Solving Vehicle Routing Problems","created":"2024-04-17","cited_by_count":24,"area":null},{"id":"2406.00415","title":"Neural Combinatorial Optimization Algorithms for Solving Vehicle Routing Problems: A Comprehensive Survey with Perspectives","created":"2024-06-01","cited_by_count":23,"area":null},{"id":"2301.03116","title":"Unsupervised Learning for Combinatorial Optimization Needs Meta-Learning","created":"2023-01-08","cited_by_count":20,"area":null},{"id":"2206.13181","title":"Learning to Control Local Search for Combinatorial Optimization","created":"2022-06-27","cited_by_count":18,"area":null},{"id":"2309.16965","title":"Controlling Continuous Relaxation for Combinatorial Optimization","created":"2023-09-29","cited_by_count":16,"area":null},{"id":"2207.03876","title":"Reinforced Lin-Kernighan-Helsgaun Algorithms for the Traveling Salesman Problems","created":"2022-07-08","cited_by_count":12,"area":null},{"id":"2506.02392","title":"Improving Generalization of Neural Combinatorial Optimization for Vehicle Routing Problems via Test-Time Projection Learning","created":"2025-06-03","cited_by_count":12,"area":null},{"id":"2205.13745","title":"DeepSAT: An EDA-Driven Learning Framework for SAT","created":"2022-05-27","cited_by_count":11,"area":null},{"id":"2406.19705","title":"DISCO: Efficient Diffusion Solver for Large-Scale Combinatorial Optimization Problems","created":"2024-06-28","cited_by_count":11,"area":null},{"id":"2503.01931","title":"Adversarial Generative Flow Network for Solving Vehicle Routing Problems","created":"2025-03-03","cited_by_count":10,"area":null},{"id":"2505.20881","title":"Generalizable Heuristic Generation Through LLMs with Meta-Optimization","created":"2025-05-27","cited_by_count":9,"area":null},{"id":"2408.12214","title":"Bridging Large Language Models and Optimization: A Unified Framework for Text-attributed Combinatorial Optimization","created":"2024-08-22","cited_by_count":8,"area":null},{"id":"2408.16717","title":"GREAT: A Graph Edge Attention Network for the Electric Vehicle Routing Problem with Asymmetric Costs","created":"2024-08-29","cited_by_count":8,"area":null},{"id":"2603.03388","title":"RADAR: Learning to Route with Asymmetry-aware DistAnce Representations","created":"2026-03-03","cited_by_count":8,"area":null},{"id":"2507.00218","title":"Learning for routing: A guided review of recent developments and future directions","created":"2025-06-30","cited_by_count":7,"area":null},{"id":"2205.01356","title":"Neural Combinatorial Optimization: a New Player in the Field","created":"2022-05-03","cited_by_count":6,"area":null},{"id":"2403.17159","title":"Less Is More -- On the Importance of Sparsification for Transformers and Graph Neural Networks for TSP","created":"2024-03-25","cited_by_count":6,"area":null},{"id":"2308.00560","title":"Reinforcement Learning-based Non-Autoregressive Solver for Traveling Salesman Problems","created":"2023-08-01","cited_by_count":5,"area":null},{"id":"2406.13125","title":"A Unified Framework for Combinatorial Optimization Based on Graph Neural Networks","created":"2024-06-19","cited_by_count":5,"area":null},{"id":"2506.16428","title":"EFormer: An Effective Edge-based Transformer for Vehicle Routing Problems","created":"2025-06-19","cited_by_count":5,"area":null},{"id":"2207.01411","title":"The Neural-Prediction based Acceleration Algorithm of Column Generation for Graph-Based Set Covering Problems","created":"2022-07-04","cited_by_count":4,"area":null},{"id":"2602.21761","title":"Survey on Neural Routing Solvers","created":"2026-02-25","cited_by_count":4,"area":null},{"id":"2210.15220","title":"End-to-End Pareto Set Prediction with Graph Neural Networks for Multi-objective Facility Location","created":"2022-10-27","cited_by_count":3,"area":null},{"id":"2302.04035","title":"Revisit the Algorithm Selection Problem for TSP with Spatial Information Enhanced Graph Neural Networks","created":"2023-02-08","cited_by_count":3,"area":null},{"id":"2411.09238","title":"Beyond the Heatmap: A Rigorous Evaluation of Component Impact in MCTS-Based TSP Solvers","created":"2024-11-14","cited_by_count":3,"area":null},{"id":"2602.16012","title":"Towards Efficient Constraint Handling in Neural Solvers for Routing Problems","created":"2026-02-17","cited_by_count":3,"area":null},{"id":"2503.12662","title":"TuneNSearch: a hybrid transfer learning and local search approach for solving vehicle routing problems","created":"2025-03-16","cited_by_count":2,"area":null},{"id":"2506.22095","title":"Beyond Simple Graphs: Neural Multi-Objective Routing on Multigraphs","created":"2025-06-27","cited_by_count":2,"area":null},{"id":"2505.19497","title":"Learning for Dynamic Combinatorial Optimization without Training Data","created":"2025-05-26","cited_by_count":1,"area":null},{"id":"2508.01557","title":"Unsupervised Learning for the Elementary Shortest Path Problem","created":"2025-08-03","cited_by_count":1,"area":null},{"id":"2110.09035","title":"Edge Rewiring Goes Neural: Boosting Network Resilience without Rich Features","created":"2021-10-18","cited_by_count":0,"area":null},{"id":"2308.09829","title":"Learning from A Single Graph is All You Need for Near-Shortest Path Routing in Wireless Networks","created":"2023-08-18","cited_by_count":0,"area":null},{"id":"2310.15516","title":"Graph Attention-based Deep Reinforcement Learning for solving the Chinese Postman Problem with Load-dependent costs","created":"2023-10-24","cited_by_count":0,"area":null},{"id":"2405.04767","title":"Test-Time Augmentation for Traveling Salesperson Problem","created":"2024-05-08","cited_by_count":0,"area":null},{"id":"2501.04747","title":"Discovering new robust local search algorithms with neuro-evolution","created":"2025-01-08","cited_by_count":0,"area":null},{"id":"2506.00533","title":"RsGCN: Subgraph-Based Rescaling Enhances Generalization of GCNs for Solving Traveling Salesman Problems","created":"2025-05-31","cited_by_count":0,"area":null},{"id":"2507.22338","title":"Parametrized Multi-Agent Routing via Deep Attention Models","created":"2025-07-30","cited_by_count":0,"area":null},{"id":"2508.08659","title":"Hybrid Node-Destroyer Model with Large Neighborhood Search for Solving the Capacitated Vehicle Routing Problem","created":"2025-08-12","cited_by_count":0,"area":null},{"id":"2508.14071","title":"Edge-Selector Model Applied for Local Search Neighborhood for Solving Vehicle Routing Problems","created":"2025-08-12","cited_by_count":0,"area":null},{"id":"2511.03137","title":"Using Multi-modal Large Language Model to Boost Fireworks Algorithm's Ability in Settling Challenging Optimization Tasks","created":"2025-11-05","cited_by_count":0,"area":null},{"id":"2512.03762","title":"RoCo: Role-Based LLMs Collaboration for Automatic Heuristic Design","created":"2025-12-03","cited_by_count":0,"area":null},{"id":"2601.19041","title":"HeatACO: A Heatmap-Guided Max--Min Ant System for Large-Scale Travelling Salesman Problems","created":"2026-01-26","cited_by_count":0,"area":null},{"id":"2601.21048","title":"Test-Time Adaptation for Unsupervised Combinatorial Optimization","created":"2026-01-28","cited_by_count":0,"area":null},{"id":"2603.11456","title":"UniHetCO: A Unified Heterogeneous Representation for Multi-Problem Learning in Unsupervised Neural Combinatorial Optimization","created":"2026-03-12","cited_by_count":0,"area":null},{"id":"2604.28102","title":"FiLMMeD: Feature-wise Linear Modulation for Cross-Problem Multi-Depot Vehicle Routing","created":"2026-04-30","cited_by_count":0,"area":null},{"id":"2607.03791","title":"TSP with Predictions: Heatmap to Tour with Provable Guarantees","created":"2026-07-04","cited_by_count":0,"area":null},{"id":"2607.18632","title":"Graph Neural Network-based Algorithm Selection for the Traveling Salesman Problem: A Systematic Study of Cost and Rank Losses under Distinct Budget Regimes","created":"2026-07-21","cited_by_count":0,"area":null},{"id":"2609.11452","title":"RouteRepair: Instance-Level Failure Diagnosis and Targeted Repair in LLM-Based Automated Heuristic Design for Routing Optimization","created":"2026-09-10","cited_by_count":0,"area":null}],"next_cursor":null}