| 2025 | AAAI | Destroy and Repair Using Hyper-Graphs for Routing. | Ke Li, Fei Liu, Zhenkun Wang, Qingfu Zhang |
| 2025 | AAAI | Multi-Objective Evolution of Heuristic Using Large Language Model. | Shunyu Yao, Fei Liu, Xi Lin, Zhichao Lu, Zhenkun Wang, Qingfu Zhang |
| 2025 | AAAI | Boundary Decomposition for Finding Nadir Objective Vector in Multi-Objective Discrete Optimization. | Ruihao Zheng, Zhenkun Wang |
| 2025 | CEC | LLM-Driven Neighborhood Search for Efficient Heuristic Design. | Zhuoliang Xie, Fei Liu, Zhenkun Wang, Qingfu Zhang |
| 2025 | CVPR | MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework. | Ping Guo, Cheng Gong, Xi Lin, Fei Liu, Zhichao Lu, Qingfu Zhang, Zhenkun Wang |
| 2025 | EMO | Large Language Model for Multiobjective Evolutionary Optimization. | Fei Liu, Xi Lin, Shunyu Yao, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang |
| 2025 | ICLR | Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization. | Xi Lin, Yilu Liu, Xiaoyuan Zhang, Fei Liu, Zhenkun Wang, Qingfu 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 | Balancing Model Efficiency and Performance: Adaptive Pruner for Long-tailed Data. | Zhe Zhao, Haibin Wen, Pengkun Wang, Shuang Wang, Zhenkun Wang, Qingfu Zhang, Yang Wang |
| 2025 | ICML | Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Design. | Zhi Zheng, Zhuoliang Xie, Zhenkun Wang, Bryan Hooi |
| 2025 | ICML | CaDA: Cross-Problem Routing Solver with Constraint-Aware Dual-Attention. | Han Li, Fei Liu, Zhi Zheng, Yu Zhang, Zhenkun Wang |
| 2025 | KDD | Co-Evolution of Large Language Models and Configuration Strategies to Enhance Surrogate-Assisted Evolutionary Algorithm. | Lindong Xie, Yang Zhang, Zhixian Tang, Edward Chung, Genghui Li, Zhenkun Wang |
| 2024 | AAAI | Learning Encodings for Constructive Neural Combinatorial Optimization Needs to Regret. | Rui Sun, Zhi Zheng, Zhenkun Wang |
| 2024 | CEC | Decomposition-Based Memetic Algorithm for Multi-Objective Fleet Size and Mix Vehicle Routing Problem. | Yunpeng Ba, Ruihao Zheng, Zhenkun Wang |
| 2024 | ICASSP | Unlocking Deep Learning: A BP-Free Approach for Parallel Block-Wise Training of Neural Networks. | Anzhe Cheng, Heng Ping, Zhenkun Wang, Xiongye Xiao, Chenzhong Yin, Shahin Nazarian, Mingxi Cheng, Paul Bogdan |
| 2024 | ICML | Smooth Tchebycheff Scalarization for Multi-Objective Optimization. | Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Fei Liu, Zhenkun Wang, Qingfu Zhang |
| 2024 | ICML | Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model. | Fei Liu, Xialiang Tong, Mingxuan Yuan, Xi Lin, Fu Luo, Zhenkun Wang, Zhichao Lu, Qingfu Zhang |
| 2024 | ICML | DPN: Decoupling Partition and Navigation for Neural Solvers of Min-max Vehicle Routing Problems. | Zhi Zheng, Shunyu Yao, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Ke Tang |
| 2024 | IJCAI | Prompt Learning for Generalized Vehicle Routing. | Fei Liu, Xi Lin, Weiduo Liao, Zhenkun Wang, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan |
| 2024 | KDD | Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization. | Fei Liu, Xi Lin, Zhenkun Wang, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan |
| 2024 | MICCAI | Tail-Enhanced Representation Learning for Surgical Triplet Recognition. | Shuangchun Gui, Zhenkun Wang |
| 2024 | PPSN | Selection Strategy Based on Proper Pareto Optimality in Evolutionary Multi-objective Optimization. | Kai Li, Kangnian Lin, Ruihao Zheng, Zhenkun Wang |
| 2024 | PPSN | Understanding the Importance of Evolutionary Search in Automated Heuristic Design with Large Language Models. | Rui Zhang, Fei Liu, Xi Lin, Zhenkun Wang, Zhichao Lu, Qingfu Zhang |
| 2023 | AAAI | A Generalized Scalarization Method for Evolutionary Multi-Objective Optimization. | Ruihao Zheng, Zhenkun Wang |
| 2023 | GECCO | Decomposition-Based Multi-Objective Evolutionary Algorithm with Model-Based Ideal Point Estimation. | Yin Wu, Ruihao Zheng, Zhenkun Wang |
| 2023 | IJCNN | Cross-Domain Few-Shot Relation Extraction via Representation Learning and Domain Adaptation. | Zhongju Yuan, Zhenkun Wang, Genghui Li |
| 2022 | GECCO | Dynamic multi-objective ensemble of acquisition functions in batch bayesian optimization. | Jixiang Chen, Fu Luo, Zhenkun Wang |
| 2021 | EMO | On the Parameter Setting of the Penalty-Based Boundary Intersection Method in MOEA/D. | Zhenkun Wang, Jingda Deng, Qingfu Zhang, Qite Yang |
| 2021 | EMO | It Is Hard to Distinguish Between Dominance Resistant Solutions and Extremely Convex Pareto Optimal Solutions. | Qite Yang, Zhenkun Wang, Hisao Ishibuchi |
| 2021 | NetSoft | Task Distribution Offloading Algorithm Based on DQN for Sustainable Vehicle Edge Network. | Tianyi Feng, Bin Wang, Haitao Zhao, Tangwei Zhang, Jiawen Tang, Zhenkun Wang |
| 2016 | CEC | Improved adaptive global replacement scheme for MOEA/D-AGR. | Hiu-Hin Tam, Man-Fai Leung, Zhenkun Wang, Sin Chun Ng, Chi-Chung Cheung, Andrew K. Lui |
| 2015 | SMC | Balancing Convergence and Diversity by Using Two Different Reproduction Operators in MOEA/D: Some Preliminary Work. | Zhenkun Wang, Qingfu Zhang, Hui Li |
| 2014 | CEC | A replacement strategy for balancing convergence and diversity in MOEA/D. | Zhenkun Wang, Qingfu Zhang, Maoguo Gong, Aimin Zhou |