Selected Publications
(# means equal contribution, * means corresponding author)
Journal Papers
Xin Jin, Nan Mi, Wen Song* and Qiqiang Li. Scheduling of Twin Automated Stacking Cranes based on Deep Reinforcement Learning. Computers & Industrial Engineering, 2024.
Wen Song, Nan Mi, Qiqiang Li, Jing Zhuang and Zhiguang Cao. Stochastic Economic Lot Scheduling via Self-Attention based Deep Reinforcement Learning. IEEE Transactions on Automation Science and Engineering (TASE), 2023.
Jingwen Li, Yining Ma, Zhiguang Cao, Yaoxin Wu, Wen Song*, Jie Zhang and Yeow Meng Che. Learning Feature Embedding Refiner for Solving Vehicle Routing Problems. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023.
Jianan Zhou, Yaoxin Wu*, Zhiguang Cao, Wen Song*, Jie Zhang and Zhenghua Chen. Learning Large Neighborhood Search for Vehicle Routing in Airport Ground Handling. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023.
Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song*, Zhang Le, Zhiguang Cao, Jie Zhang. A review on learning to solve combinatorial optimisation problems in manufacturing. IET Collaborative Intelligent Manufacturing, 2023.
Wen Song, Yi Liu, Zhiguang Cao, Yaoxin Wu and Qiqiang li. Instance-specific algorithm configuration via unsupervised deep graph clustering. Engineering Applications of Artificial Intelligence, 2023.
Xin Jin, Zhentang Duan, Wen Song* and Qiqiang Li*. Container stacking optimization based on Deep Reinforcement Learning. Engineering Applications of Artificial Intelligence, 2023.
Zhizheng Zhang, Wen Song*, Qiqiang Li* and Hui Gao. Multiscale global and local self-attention-based network for remaining useful life prediction. Measurement Science and Technology, 2023.
Wen Song, Xinyang Chen, Qiqiang Li and Zhiguang Cao. Flexible Job Shop Scheduling via Graph Neural Network and Deep Reinforcement Learning. IEEE Transactions on Industrial Informatics (TII), 2022.
Wen Song, Zhiguang Cao, Jie Zhang and Andrew Lim. Learning Variable Ordering Heuristics for Solving Constraint Satisfaction Problems. Engineering Applications of Artificial Intelligence, 2022.
Rongkai Zhang, Cong Zhang, Zhiguang Cao, Wen Song*, Puay Siew Tan, Jie Zhang, Bihan Wen and Justin Dauwels. Learning to Solve Multiple-TSP with Time Window and Rejection via Deep Reinforcement Learning. IEEE Transactions on Intelligent Transportation Systems (TITS), 2022.
Zhizheng Zhang, Wen Song* and Qiqiang Li*. Dual Aspect Self-Attention based on Transformer for Remaining Useful Life Prediction. IEEE Transactions on Instrumentation and Measurement (TIM), 2022
Zhonghao Zhang, Qiqiang Li*, Wen Song*, Pengfei Wei, Jing Guo. A novel concavity based method for automatic segmentation of touching cells in microfluidic chips. Expert Systems with Applications, 2022.
Yaoxin Wu, Wen Song*, Zhiguang Cao*, Jie Zhang and Andrew Lim. Learning Improvement Heuristics for Solving Routing Problems. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021.
Zhiguang Cao, Tingbo Liao, Wen Song*, Zhenghua Chen and Chongshou Li. Detecting the shuttlecock for a badminton robot: A YOLO based approach. Expert Systems with Applications, 2021.
Jingwen Li, Yining Ma, Ruize Gao, Zhiguang Cao, Andrew Lim, Wen Song and Jie Zhang. Deep reinforcement learning for solving the heterogeneous capacitated vehicle routing problem. IEEE Transactions on Cybernetics (TCyb), 2021.
Jingwen Li, Liang Xin, Zhiguang Cao, Andrew Lim, Wen Song and Jie Zhang. Heterogeneous Attentions for Solving Pickup and Delivery Problem via Deep Reinforcement Learning. IEEE Transactions on Intelligent Transportation Systems (TITS), 2021.
Yunyun Niu, Yongpeng Zhang, Zhiguang Cao, Kaizhou Gao, Jianhua Xiao, Wen Song and Fangwei Zhang. MIMOA: A membrane-inspired multi-objective algorithm for green vehicle routing problem with stochastic demands. Swarm and Evolutionary Computation, 2021.
Liang Xin, Wen Song*, Zhiguang Cao and Jie Zhang. Step-wise Deep Learning Models for Solving Routing Problems. IEEE Transactions on Industrial Informatics (TII), 2020.
Zhiguang Cao, Hongliang Guo, Wen Song, Kaizhou Gao, Zhenghua Chen, Le Zhang and Xuexi Zhang. Using Reinforcement Learning to Minimize the Probability of Delay Occurrence in Transportation. IEEE Transactions on Vehicular Technology (TVT), 2020.
Zhiguang Cao, Hongliang Guo, Wen Song, Kaizhou Gao, Liujiang Kang, Xuexi Zhang and Qilun Wu. Improving the Performance of Transportation Networks: A Semi-Centralized Pricing Approach. IEEE Transactions on Intelligent Transportation Systems (TITS), 2020.
Chao Ma, Zhenbing Liu, Zhiguang Cao, Wen Song, Jie Zhang and Weiliang Zeng. Cost-sensitive Deep Forest for Price Prediction. Pattern Recognition, 2020.
Wen Song, Donghun Kang, Jie Zhang, Zhiguang Cao and Hui Xi. A Sampling Approach for Proactive Project Scheduling under Generalized Time-dependent Workability Uncertainty. Journal of Artificial Intelligence Research (JAIR), 64:385-427, 2019.
Luhao Wang, Bingying Zhang, Qiqiang Li, Wen Song and Guanguan Li. Robust distributed optimization for energy dispatch of multi-stakeholdermultiple microgrids under uncertainty. Applied Energy, 2019.
WenSong, Hui Xi, Donghun Kang and Jie Zhang. An Agent-based Simulation System for Multi-Project Scheduling under Uncertainty. Simulation Modelling Practice and Theory, 86:187-203, 2018.
Wen Song, Donghun Kang, Jie Zhang and Hui Xi. A Multi-Unit Combinatorial Auction based Approach for Decentralized Multi-Project Scheduling. Journal of Autonomous Agents and Multiagent Systems (JAAMAS), 31:1548–1577, 2017.
Conference Papers
Yu Sun, Kai Wang, Zhipeng Hu, Runze Wu, Yaoxin Wu, Wen Song*, Xudong Shen, Tangjie Lv, and Changjie Fan. MGMatch: Fast Matchmaking with Nonlinear Objective and Constraints via Multimodal Deep Graph Learning. The 30th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024.
Cong Zhang, Zhiguang Cao, Wen Song*, Yaoxin Wu, and Jie Zhang. Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling. International Conference on Learning Representations (ICLR), 2024.
Cong Zhang, Zhiguang Cao, Yaoxin Wu, Wen Song*, and Jing Sun. Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem The 40th Conference on Uncertainty in Artificial Intelligence (UAI), 2024.
Yuan Jiang, Zhiguang Cao, Yaoxin Wu, Wen Song*, and Jie Zhang. Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift. Advances in Neural Information Processing Systems (NeurIPS), 2023.
Jianan Zhou, Yaoxin Wu*, Wen Song*, Zhiguang Cao, and Jie Zhang. Towards Omni-generalizable Neural Methods for Vehicle Routing Problems. International Conference on Machine Learning (ICML), 2023.
Xinjie Liang, Wen Song*, and Pengfei Wei. Dynamic Job Shop Scheduling via Deep Reinforcement Learning. The 35th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2023.
Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, Abhishek Gupta, and Mingyan Simon Lin. Graph Learning Assisted Multi-Objective Integer Programming. Advances in Neural Information Processing Systems (NeurIPS), 2022.
Yining Ma, Jingwen Li, Zhiguang Cao, Wen Song, Hongliang Guo, Yuejiao Gong, and Yeow Meng Chee. Efficient Neural Neighbourhood Search for Pickup and Delivery Problems. 31st International Joint Conference on Artificial Intelligence (IJCAI), 2022.
Yaoxin Wu, Wen Song(#), Zhiguang Cao, and Jie Zhang. Learning Scenario Representation for Solving Two-stage Stochastic Integer Programs. International Conference on Learning Representations (ICLR), 2022.
Xiaohan Zhao, Wen Song*, Qiqiang Li, Huadong Shi, Zhichao Kang and Chunmei Zhang. A Deep Reinforcement Learning Approach for Resource-Constrained Project Scheduling. IEEE Symposium Series on Computational Intelligence (SSCI), 2022.
Pengfei Wei, Xinghua Qu, Wen Song and Zejun Ma. Dynamic Transfer Gaussian Process Regression. 31st ACM International Conference on Information & Knowledge Management (CIKM), 2022.
Yaoxin Wu, Wen Song*, Zhiguang Cao, and Jie Zhang. Learning Large Neighborhood Search Policy for Integer Programming. Advances in Neural Information Processing Systems (NeurIPS), 2021.
Liang Xin, Wen Song, Zhiguang Cao, and Jie Zhang. NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem. Advances in Neural Information Processing Systems (NeurIPS), 2021.
Yining Ma, Jingwen Li, Zhiguang Cao*, Wen Song*, Le Zhang, Zhenghua Chen, and Jing Tang. Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer. Advances in Neural Information Processing Systems (NeurIPS), 2021.
Liang Xin(#), Wen Song(#), Zhiguang Cao and Jie Zhang. Multi-Decoder Attention Model with Embedding Glimpse for Solving Vehicle Routing Problems. 35th AAAI Conference on Artificial Intelligence (AAAI), 2021.
Cong Zhang(#), Wen Song(#), Zhiguang Cao, Jie Zhang, Puay Siew Tan and Chi Xu. Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning. Advances in Neural Information Processing Systems (NeurIPS), 2020.
Sa Gao, Chunyang Chen, Zhenchang Xing, Yukun Ma, Wen Song and Shang-Wei Lin. A neural model for method name generation from functional description. IEEE 26th International Conference on Software Analysis, Evolution and Reengineering (SANER), 2019.
Wen Song, Donghun Kang, Jie Zhang and Hui Xi. Risk-aware Proactive Scheduling via Conditional Value-at-Risk. Thirty-second AAAI Conference on Artificial Intelligence (AAAI), 2018. (Oral presentation)
Donghun Kang, Zhenchao Bing, Wen Song, Zehong Hu, Shuo Chen, Jie Zhang and Hui Xi. Automatic Construction of Agent-based Simulation Using Business Process Diagrams and Ontology-based Models (Demo). 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2017.
Wen Song, Donghun Kang, Jie Zhang and Hui Xi. Proactive Project Scheduling with Time-dependent Workability Uncertainty. 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2017.
Wen Song, Donghun Kang, Jie Zhang and Hui Xi. A Sampling based Approach for Proactive Project Scheduling with Time-dependent Duration Uncertainty (Student Abstract). Thirty-first AAAI Conference on Artificial Intelligence (AAAI), 2017.
Wen Song. Project Scheduling in Complex Business Environment (Doctoral Consortium). Thirty-first AAAI Conference on Artificial Intelligence (AAAI), 2017.
Wen Song. An Auction-based Approach for Decentralized Multi-Project Scheduling (Doctoral Consortium). 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2016.
Wen Song, Donghun Kang, Jie Zhang and Hui Xi. Decentralized Multi-Project Scheduling via Multi-Unit Combinatorial Auction. 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2016.