{"total":71,"rows":[{"id":"2312.08224","title":"GLOP: Learning Global Partition and Local Construction for Solving Large-scale Routing Problems in Real-time","created":"2023-12-13","cited_by_count":85,"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":"2405.01029","title":"MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts","created":"2024-05-02","cited_by_count":70,"area":"moe"},{"id":"2406.15007","title":"RouteFinder: Towards Foundation Models for Vehicle Routing Problems","created":"2024-06-21","cited_by_count":55,"area":null},{"id":"2503.00753","title":"Rethinking Light Decoder-based Solvers for Vehicle Routing Problems","created":"2025-03-02","cited_by_count":37,"area":"deeprl"},{"id":"2402.14048","title":"PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization","created":"2024-02-21","cited_by_count":35,"area":"deeprl"},{"id":"2410.21066","title":"Learning to Handle Complex Constraints for Vehicle Routing Problems","created":"2024-10-28","cited_by_count":29,"area":null},{"id":"2509.16865","title":"Large Language Models as End-to-end Combinatorial Optimization Solvers","created":"2025-09-21","cited_by_count":28,"area":null},{"id":"2501.03715","title":"Neural Deconstruction Search for Vehicle Routing Problems","created":"2025-01-07","cited_by_count":15,"area":null},{"id":"2405.04657","title":"ACEGEN: Reinforcement learning of generative chemical agents for drug discovery","created":"2024-05-07","cited_by_count":14,"area":"deeprl"},{"id":"2503.16159","title":"RRNCO: Towards Real-World Routing with Neural Combinatorial Optimization","created":"2025-03-20","cited_by_count":11,"area":null},{"id":"2505.16952","title":"FrontierCO: Real-World and Large-Scale Evaluation of Machine Learning Solvers for Combinatorial Optimization","created":"2025-05-22","cited_by_count":11,"area":null},{"id":"2410.04968","title":"Collaboration! Towards Robust Neural Methods for Routing Problems","created":"2024-10-07","cited_by_count":9,"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":"2403.07559","title":"Ensembling Prioritized Hybrid Policies for Multi-agent Pathfinding","created":"2024-03-12","cited_by_count":7,"area":null},{"id":"2405.08424","title":"Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More","created":"2024-05-14","cited_by_count":7,"area":null},{"id":"2409.03811","title":"PARCO: Parallel AutoRegressive Models for Multi-Agent Combinatorial Optimization","created":"2024-09-05","cited_by_count":7,"area":null},{"id":"2510.07073","title":"VRPAgent: LLM-Driven Discovery of Heuristic Operators for Vehicle Routing Problems","created":"2025-10-08","cited_by_count":7,"area":null},{"id":"2506.08898","title":"Preference-Driven Multi-Objective Combinatorial Optimization with Conditional Computation","created":"2025-06-10","cited_by_count":6,"area":"deeprl"},{"id":"2507.10614","title":"Fine-tuning Large Language Model for Automated Algorithm Design","created":"2025-07-13","cited_by_count":6,"area":null},{"id":"2410.09693","title":"Neural Solver Selection for Combinatorial Optimization","created":"2024-10-13","cited_by_count":5,"area":null},{"id":"2503.01919","title":"Reinforcement learning with combinatorial actions for coupled restless bandits","created":"2025-03-01","cited_by_count":5,"area":"deeprl"},{"id":"2507.01037","title":"Learning to Segment for Vehicle Routing Problems","created":"2025-06-22","cited_by_count":5,"area":null},{"id":"2510.16701","title":"An Agentic Framework with LLMs for Solving Complex Vehicle Routing Problems","created":"2025-10-19","cited_by_count":5,"area":"agents"},{"id":"2502.01459","title":"Learning to Partially Defer for Sequences","created":"2025-02-03","cited_by_count":4,"area":null},{"id":"2503.10421","title":"Learning Constraints-Based Adaptive Hypergraph Neural Networks for Solving Vehicle Routing Problems","created":"2025-03-13","cited_by_count":3,"area":"deeprl"},{"id":"2505.17938","title":"LMask: Learn to Solve Constrained Routing Problems with Lazy Masking","created":"2025-05-23","cited_by_count":3,"area":null},{"id":"2510.21693","title":"Mechanistic Interpretability for Neural TSP Solvers","created":"2025-10-24","cited_by_count":3,"area":"mechinterp"},{"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":"2310.16397","title":"Learning Efficient Surrogate Dynamic Models with Graph Spline Networks","created":"2023-10-25","cited_by_count":2,"area":null},{"id":"2502.10233","title":"Learning to Solve the Min-Max Mixed-Shelves Picker-Routing Problem via Hierarchical and Parallel Decoding","created":"2025-02-14","cited_by_count":2,"area":null},{"id":"2504.06126","title":"Accelerating Vehicle Routing via AI-Initialized Genetic Algorithms","created":"2025-04-08","cited_by_count":2,"area":"deeprl"},{"id":"2511.09219","title":"Planning in Branch-and-Bound: Model-Based Reinforcement Learning for Exact Combinatorial Optimization","created":"2025-11-12","cited_by_count":2,"area":"deeprl"},{"id":"2505.05119","title":"USPR: Learning a Unified Solver for Profiled Routing","created":"2025-05-08","cited_by_count":1,"area":null},{"id":"2509.05084","title":"Recurrent State Encoders for Efficient Neural Combinatorial Optimization","created":"2025-09-05","cited_by_count":1,"area":null},{"id":"2509.12643","title":"Learn to Relax with Large Language Models: Solving Constraint Optimization Problems via Bidirectional Coevolution","created":"2025-09-16","cited_by_count":1,"area":null},{"id":"2509.23465","title":"ViTSP: A Vision Language Models Guided Framework for Solving Large-Scale Traveling Salesman Problems","created":"2025-09-27","cited_by_count":1,"area":"mllm"},{"id":"2606.10321","title":"Baseline-Free Policy Optimization for Neural Combinatorial Optimization","created":"2026-06-09","cited_by_count":1,"area":"lr"},{"id":"2609.07990","title":"HyCO: A Hybrid Neural Solver for Combinatorial Optimization","created":"2026-09-07","cited_by_count":1,"area":"diffusion"},{"id":"2411.04777","title":"Learn to Solve Vehicle Routing Problems ASAP: A Neural Optimization Approach for Time-Constrained Vehicle Routing Problems with Finite Vehicle Fleet","created":"2024-11-07","cited_by_count":0,"area":null},{"id":"2411.14411","title":"Multi-Agent Environments for Vehicle Routing Problems","created":"2024-11-21","cited_by_count":0,"area":null},{"id":"2501.05667","title":"TransPlace: Transferable Circuit Global Placement via Graph Neural Network","created":"2025-01-10","cited_by_count":0,"area":null},{"id":"2503.04085","title":"SED2AM: Solving Multi-Trip Time-Dependent Vehicle Routing Problem using Deep Reinforcement Learning","created":"2025-03-06","cited_by_count":0,"area":"deeprl"},{"id":"2506.06094","title":"Onboard Mission Replanning for Adaptive Cooperative Multi-Robot Systems","created":"2025-06-06","cited_by_count":0,"area":null},{"id":"2506.16732","title":"On Training-Test (Mis)alignment in Unsupervised Combinatorial Optimization: Observation, Empirical Exploration, and Analysis","created":"2025-06-20","cited_by_count":0,"area":null},{"id":"2508.08493","title":"POMO+: Leveraging starting nodes in POMO for solving Capacitated Vehicle Routing Problem","created":"2025-08-11","cited_by_count":0,"area":"deeprl"},{"id":"2509.16938","title":"NeuFACO: Neural Focused Ant Colony Optimization for Traveling Salesman Problem","created":"2025-09-21","cited_by_count":0,"area":"deeprl"},{"id":"2509.18930","title":"Tackling GNARLy Problems: Graph Neural Algorithmic Reasoning Reimagined through Reinforcement Learning","created":"2025-09-23","cited_by_count":0,"area":null},{"id":"2510.03065","title":"A Unified Deep Reinforcement Learning Approach for Close Enough Traveling Salesman Problem","created":"2025-10-03","cited_by_count":0,"area":"deeprl"},{"id":"2510.12273","title":"Multi-Action Self-Improvement for Neural Combinatorial Optimization","created":"2025-10-14","cited_by_count":0,"area":null},{"id":"2510.19348","title":"A Markov Decision Process for Variable Selection in Branch & Bound","created":"2025-10-22","cited_by_count":0,"area":null},{"id":"2512.24251","title":"Deep Reinforcement Learning for Solving the Fleet Size and Mix Vehicle Routing Problem","created":"2025-12-30","cited_by_count":0,"area":"deeprl"},{"id":"2603.06260","title":"Learning to Solve Orienteering Problem with Time Windows and Variable Profits","created":"2026-03-06","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":"2603.20702","title":"Decoupling Numerical and Structural Parameters: An Empirical Study on Adaptive Genetic Algorithms via Deep Reinforcement Learning for the Large-Scale TSP","created":"2026-03-21","cited_by_count":0,"area":"deeprl"},{"id":"2603.28385","title":"Critic-Free Deep Reinforcement Learning for Maritime Coverage Path Planning on Irregular Hexagonal Grids","created":"2026-03-30","cited_by_count":0,"area":"deeprl"},{"id":"2604.15202","title":"Benchmarking Classical Coverage Path Planning Heuristics on Irregular Hexagonal Grids for Maritime Coverage Scenarios","created":"2026-04-16","cited_by_count":0,"area":null},{"id":"2605.06332","title":"LINC: Decoupling Local Consequence Scoring from Hidden Matching in Constructive Neural Routing","created":"2026-05-07","cited_by_count":0,"area":null},{"id":"2605.13638","title":"CO-MAP: A Reinforcement Learning Approach to the Qubit Allocation Problem","created":"2026-05-13","cited_by_count":0,"area":"deeprl"},{"id":"2605.14624","title":"An Amortized Efficiency Threshold for Comparing Neural and Heuristic Solvers in Combinatorial Optimization","created":"2026-05-14","cited_by_count":0,"area":null},{"id":"2605.18094","title":"Learning to Solve Compositional Geometry Routing Problems","created":"2026-05-18","cited_by_count":0,"area":null},{"id":"2605.24914","title":"MVR-cache: Optimizing Semantic Caching via Multi-Vector Retrieval and Learned Prompt Segmentation","created":"2026-05-24","cited_by_count":0,"area":null},{"id":"2605.25235","title":"Constraint-Anchored Attribution: Feasibility-Certified Counterfactuals and Bonferroni-PAC Sufficient Subsets for Neural CO Policies","created":"2026-05-24","cited_by_count":0,"area":null},{"id":"2605.27027","title":"SQARL: A Size-Agnostic Reinforcement Learning approach for Circuit Allocation in Distributed Quantum Architectures","created":"2026-05-26","cited_by_count":0,"area":"deeprl"},{"id":"2606.04039","title":"Beyond Static Priors: Dynamic Neural Guidance for Large-Scale Ant Colony Optimization","created":"2026-06-02","cited_by_count":0,"area":null},{"id":"2606.10611","title":"Geometry-Aware Reinforcement Learning for 2D Irregular Nesting","created":"2026-06-09","cited_by_count":0,"area":"deeprl"},{"id":"2606.17266","title":"SkillChain-Gym: A Benchmark for Reskilling-Aware Production-Inventory Control under Disruptions","created":"2026-06-15","cited_by_count":0,"area":null},{"id":"2607.04487","title":"Two Black Boxes, One Solver: Encoder Probing and Decoder Attribution for Neural Multi-Attribute VRP under Hard-Mask and Recourse Decoders","created":"2026-07-05","cited_by_count":0,"area":null},{"id":"2609.25728","title":"Self-Supervised Combinatorial Optimization with Constraints via Frank-Wolfe","created":"2026-09-22","cited_by_count":0,"area":null},{"id":"2609.37175","title":"VLM Fine-Tuning for End-to-End Combinatorial Optimization","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.15106","title":"RELAGRAM: Recursive Latent Graph Model for the Capacitated Vehicle Routing Problem","created":"2026-10-10","cited_by_count":0,"area":null}],"next_cursor":null}