| 2026 | AAAI | Bridging Synthetic and Real Routing Problems via LLM-Guided Instance Generation and Progressive Adaptation. | Jianghan Zhu, Yaoxin Wu, Zhuoyi Lin, Zhengyuan Zhang, Haiyan Yin, Zhiguang Cao, Senthilnath Jayavelu, Xiaoli Li |
| 2026 | ACL | Reasoning in a Combinatorial and Constrained World: Benchmarking LLMs on Natural-Language Combinatorial Optimization. | Xia Jiang, Jing Chen, Cong Zhang, Jie Gao, Chengpeng Hu, Chenhao Zhang, Yaoxin Wu, Yingqian Zhang |
| 2026 | CPAIOR | Towards Solving Polynomial-Objective Integer Programming with Hypergraph Neural Networks. | Minshuo Li, Yaoxin Wu, Pavel Troubil, Yingqian Zhang, Wim P. M. Nuijten |
| 2025 | AAAI | Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems. | Igor G. Smit, Yaoxin Wu, Pavel Troubil, Yingqian Zhang, Wim P. M. Nuijten |
| 2025 | ECAI | Search Trajectory Network-Enhanced Multi-Objective Dynamic Algorithm Configuration. | Robbert Reijnen, Zaharah Bukhsh, Hoong Chuin Lau, Yaoxin Wu, Yingqian Zhang |
| 2025 | ICLR | Rethinking Neural Multi-Objective Combinatorial Optimization via Neat Weight Embedding. | Jinbiao Chen, Zhiguang Cao, Jiahai Wang, Yaoxin Wu, Hanzhang Qin, Zizhen Zhang, Yue-Jiao Gong |
| 2025 | ICLR | Neural Multi-Objective Combinatorial Optimization via Graph-Image Multimodal Fusion. | Jinbiao Chen, Jiahai Wang, Zhiguang Cao, Yaoxin Wu |
| 2025 | ICLR | DRoC: Elevating Large Language Models for Complex Vehicle Routing via Decomposed Retrieval of Constraints. | Xia Jiang, Yaoxin Wu, Chenhao Zhang, Yingqian Zhang |
| 2025 | ICLR | Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems. | Fu Luo, Xi Lin, Yaoxin Wu, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang |
| 2025 | ICML | Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization. | Robbert Reijnen, Yaoxin Wu, Zaharah Bukhsh, Yingqian Zhang |
| 2025 | IJCAI | EFormer: An Effective Edge-based Transformer for Vehicle Routing Problems. | Dian Meng, Zhiguang Cao, Yaoxin Wu, Yaqing Hou, Hongwei Ge, Qiang Zhang |
| 2025 | IJCAI | Preference-based Deep Reinforcement Learning for Historical Route Estimation. | Boshen Pan, Yaoxin Wu, Zhiguang Cao, Yaqing Hou, Guangyu Zou, Qiang Zhang |
| 2025 | KDD | Diversity Optimization for Travelling Salesman Problem via Deep Reinforcement Learning. | Qi Li, Zhiguang Cao, Yining Ma, Yaoxin Wu, Yue-Jiao Gong |
| 2024 | ICLR | Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling. | Cong Zhang, Zhiguang Cao, Wen Song, Yaoxin Wu, Jie Zhang |
| 2024 | ICML | MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts. | Jianan Zhou, Zhiguang Cao, Yaoxin Wu, Wen Song, Yining Ma, Jie Zhang, Chi Xu |
| 2024 | IJCAI | Cross-Problem Learning for Solving Vehicle Routing Problems. | Zhuoyi Lin, Yaoxin Wu, Bangjian Zhou, Zhiguang Cao, Wen Song, Yingqian Zhang, Senthilnath Jayavelu |
| 2024 | KDD | MGMatch: Fast Matchmaking with Nonlinear Objective and Constraints via Multimodal Deep Graph Learning. | Yu Sun, Kai Wang, Zhipeng Hu, Runze Wu, Yaoxin Wu, Wen Song, Xudong Shen, Tangjie Lv, Changjie Fan |
| 2024 | UAI | Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem. | Cong Zhang, Zhiguang Cao, Yaoxin Wu, Wen Song, Jing Sun |
| 2023 | ICML | Towards Omni-generalizable Neural Methods for Vehicle Routing Problems. | Jianan Zhou, Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang |
| 2023 | UAI | Multi-view graph contrastive learning for solving vehicle routing problems. | Yuan Jiang, Zhiguang Cao, Yaoxin Wu, Jie Zhang |
| 2022 | AAAI | Learning to Solve Routing Problems via Distributionally Robust Optimization. | Yuan Jiang, Yaoxin Wu, Zhiguang Cao, Jie Zhang |
| 2022 | ICLR | NASPY: Automated Extraction of Automated Machine Learning Models. | Xiaoxuan Lou, Shangwei Guo, Jiwei Li, Yaoxin Wu, Tianwei Zhang |
| 2022 | ICLR | Learning Scenario Representation for Solving Two-stage Stochastic Integer Programs. | Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang |