PPaperPicks

Yaoxin Wu

25 papers at tracked venues · 19 at CORE A* · active 20242026

Venues

Frequent coauthors

Papers

  1. Bridging Synthetic and Real Routing Problems via LLM-Guided Instance Generation and Progressive Adaptation
  2. Reasoning in a Combinatorial and Constrained World: Benchmarking LLMs on Natural-Language Combinatorial Optimization
  3. Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems
  4. DRoC: Elevating Large Language Models for Complex Vehicle Routing via Decomposed Retrieval of Constraints
  5. Diversity Optimization for Travelling Salesman Problem via Deep Reinforcement Learning
  6. EFormer: An Effective Edge-based Transformer for Vehicle Routing Problems
  7. Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization
  8. Large Language Models as End-to-end Combinatorial Optimization Solvers
  9. MTL-KD: Multi-Task Learning Via Knowledge Distillation for Generalizable Neural Vehicle Routing Solver
  10. Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems
  11. Neural Multi-Objective Combinatorial Optimization via Graph-Image Multimodal Fusion
  12. Preference-Driven Multi-Objective Combinatorial Optimization with Conditional Computation
  13. Preference-based Deep Reinforcement Learning for Historical Route Estimation
  14. Rethinking Neural Combinatorial Optimization for Vehicle Routing Problems with Different Constraint Tightness Degrees
  15. Rethinking Neural Multi-Objective Combinatorial Optimization via Neat Weight Embedding
  16. Search Trajectory Network-Enhanced Multi-Objective Dynamic Algorithm Configuration
  17. UniteFormer: Unifying Node and Edge Modalities in Transformers for Vehicle Routing Problems
  18. Collaboration! Towards Robust Neural Methods for Routing Problems
  19. Collaborative Deep Reinforcement Learning for Solving Multi-Objective Vehicle Routing Problems
    AAMAS 2024 · Yaoxin Wu
  20. Cross-Problem Learning for Solving Vehicle Routing Problems
  21. Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
  22. Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem
  23. Learning to Handle Complex Constraints for Vehicle Routing Problems
  24. MGMatch: Fast Matchmaking with Nonlinear Objective and Constraints via Multimodal Deep Graph Learning
  25. MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts