papers

Publications (49)

cs.LG2025

MTL-KD: Multi-Task Learning Via Knowledge Distillation for Generalizable Neural Vehicle Routing Solver

Yuepeng Zheng, Fu Luo, Zhenkun Wang +2

cs.AI2023

Learning Large Neighborhood Search for Vehicle Routing in Airport Ground Handling

Jianan Zhou, Yaoxin Wu, Zhiguang Cao +3

cs.LG2026

Generalizable Heuristic Generation Through LLMs with Meta-Optimization

Yiding Shi, Jianan Zhou, Wen Song +4

cs.IR2024

Hypergrah-Enhanced Dual Convolutional Network for Bundle Recommendation

Yang Li, Kangbo Liu, Yaoxin Wu +3

cs.AI2026

DRAGON: LLM-Driven Decomposition and Reconstruction Agents for Large-Scale Combinatorial Optimization

Shengkai Chen, Zhiguang Cao, Jianan Zhou +5

cs.LG2023

Neural Multi-Objective Combinatorial Optimization with Diversity Enhancement

Jinbiao Chen, Zizhen Zhang, Zhiguang Cao +4

cs.AI2025

Job Shop Scheduling Benchmark: Environments and Instances for Learning and Non-learning Methods

Robbert Reijnen, Igor G. Smit, Hongxiang Zhang +3

cs.AI2026

Reasoning in a Combinatorial and Constrained World: Benchmarking LLMs on Natural-Language Combinatorial Optimization

Xia Jiang, Jing Chen, Cong Zhang +5

cs.LG2025

Enhancing the Cross-Size Generalization for Solving Vehicle Routing Problems via Continual Learning

Jingwen Li, Zhiguang Cao, Yaoxin Wu +1

cs.AI2021

Learning Large Neighborhood Search Policy for Integer Programming

Yaoxin Wu, Wen Song, Zhiguang Cao +1

cs.AI2024

Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems

Igor G. Smit, Yaoxin Wu, Pavel Troubil +2

cs.LG2024

Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem

Cong Zhang, Zhiguang Cao, Yaoxin Wu +2

cs.AI2024

Graph Neural Networks for Job Shop Scheduling Problems: A Survey

Igor G. Smit, Jianan Zhou, Robbert Reijnen +6

cs.LG2025

Diversity Optimization for Travelling Salesman Problem via Deep Reinforcement Learning

Qi Li, Zhiguang Cao, Yining Ma +2

cs.AI2026

Aligning LLMs with Graph Neural Solvers for Combinatorial Optimization

Shaodi Feng, Zhuoyi Lin, Yaoxin Wu +4

cs.CV2025

Multimodal Attention-Aware Fusion for Diagnosing Distal Myopathy: Evaluating Model Interpretability and Clinician Trust

Mohsen Abbaspour Onari, Lucie Charlotte Magister, Yaoxin Wu +10

cs.LG2025

Reinforcement Learning for Solving the Pricing Problem in Column Generation: Applications to Vehicle Routing

Abdo Abouelrous, Laurens Bliek, Adriana F. Gabor +2

cs.LG2026

Automated Reinforcement Learning: An Overview

Reza Refaei Afshar, Joaquin Vanschoren, Uzay Kaymak +4

cs.AI2024

Bridging Large Language Models and Optimization: A Unified Framework for Text-attributed Combinatorial Optimization

Xia Jiang, Yaoxin Wu, Yuan Wang +1

cs.AI2026

Bridging Synthetic and Real Routing Problems via LLM-Guided Instance Generation and Progressive Adaptation

Jianghan Zhu, Yaoxin Wu, Zhuoyi Lin +5

cs.LG2026

Learning with Foresight: Enhancing Neural Routing Policy via Multi-Node Lookahead Prediction

Xia Jiang, Yaoxin Wu, Yew-Soon Ong +1

cs.LG2022

Learning to Solve Routing Problems via Distributionally Robust Optimization

Yuan Jiang, Yaoxin Wu, Zhiguang Cao +1

cs.NE2026

Towards Solving Polynomial-Objective Integer Programming with Hypergraph Neural Networks

Minshuo Li, Yaoxin Wu, Pavel Troubil +2

cs.AI2026

Preference-Driven Multi-Objective Combinatorial Optimization with Conditional Computation

Mingfeng Fan, Jianan Zhou, Yifeng Zhang +3

cs.AI2024

Collaboration! Towards Robust Neural Methods for Routing Problems

Jianan Zhou, Yaoxin Wu, Zhiguang Cao +3

cs.LG2024

Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling

Cong Zhang, Zhiguang Cao, Wen Song +2

cs.LG2026

Adversarial Instance Generation and Robust Training for Neural Combinatorial Optimization with Multiple Objectives

Wei Liu, Yaoxin Wu, Yingqian Zhang +2

cs.AI2025

Large Language Models as End-to-end Combinatorial Optimization Solvers

Xia Jiang, Yaoxin Wu, Minshuo Li +2

cs.LG2023

Towards Omni-generalizable Neural Methods for Vehicle Routing Problems

Jianan Zhou, Yaoxin Wu, Wen Song +2

cs.AI2026

Towards Efficient Constraint Handling in Neural Solvers for Routing Problems

Jieyi Bi, Zhiguang Cao, Jianan Zhou +5

cs.AI2024

Learning to Handle Complex Constraints for Vehicle Routing Problems

Jieyi Bi, Yining Ma, Jianan Zhou +4

cs.NE2025

Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization

Robbert Reijnen, Yaoxin Wu, Zaharah Bukhsh +1

cs.LG2025

Rethinking Neural Combinatorial Optimization for Vehicle Routing Problems with Different Constraint Tightness Degrees

Fu Luo, Yaoxin Wu, Zhi Zheng +1

cs.HC2026

LLMs for Human Mobility: Opportunities, Challenges, and Future Directions

Jie Gao, Yaoxin Wu

cs.AI2026

Enhancing Cross-Problem Vehicle Routing via Federated Learning

Xiangchi Meng, Jianan Zhou, Jie Gao +4

cs.AI2024

MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts

Jianan Zhou, Zhiguang Cao, Yaoxin Wu +4

cs.LG2025

EFormer: An Effective Edge-based Transformer for Vehicle Routing Problems

Dian Meng, Zhiguang Cao, Yaoxin Wu +3

cs.LG2025

End-to-end Deep Reinforcement Learning for Stochastic Multi-objective Optimization in C-VRPTW

Abdo Abouelrous, Laurens Bliek, Yaoxin Wu +1

cs.LG2025

Graph Reduction with Unsupervised Learning in Column Generation: A Routing Application

Abdo Abouelrous, Laurens Bliek, Adriana F. Gabor +2

cs.AI2024

Cross-Problem Learning for Solving Vehicle Routing Problems

Zhuoyi Lin, Yaoxin Wu, Bangjian Zhou +4

cs.AI2026

AnalogAgent: Self-Improving Analog Circuit Design Automation with LLM Agents

Zhixuan Bao, Zhuoyi Lin, Jiageng Wang +5

cs.LG2025

Partial Column Generation with Graph Neural Networks for Team Formation and Routing

Giacomo Dall'Olio, Rainer Kolisch, Yaoxin Wu

cs.AI2020

Learning Improvement Heuristics for Solving Routing Problems

Yaoxin Wu, Wen Song, Zhiguang Cao +2

cs.AI2026

Learning Scenario Reduction for Two-Stage Robust Optimization with Discrete Uncertainty

Tianjue Lin, Jianan Zhou, Jieyi Bi +4

cs.AI2023

Neural Airport Ground Handling

Yaoxin Wu, Jianan Zhou, Yunwen Xia +3

cs.AI2026

A General Neural Backbone for Mixed-Integer Linear Optimization via Dual Attention

Peixin Huang, Yaoxin Wu, Yining Ma +3

cs.LG2026

MViewRouter: Internalizing Geometric Equivariance via Multi-view Alternating Attention for Combinatorial Routing

Shiyan Liu, Bohan Tan, Yaoxin Wu +1

cs.LG2026

Mamba Meets Scheduling: Learning to Solve Flexible Job Shop Scheduling with Efficient Sequence Modeling

Zhi Cao, Cong Zhang, Yaoxin Wu +2

cs.LG2025

A Unified Deep Reinforcement Learning Approach for Close Enough Traveling Salesman Problem

Mingfeng Fan, Jiaqi Cheng, Yaoxin Wu +4