Zhiguang Cao bio photo

Zhiguang Cao

Assistant Professor, School of Computing and Information Systems, Singapore Management University.

Singapore   G. Scholar e-Mail

Publications

Conference Papers

  1. [L2Opt, VRP] Diversity Optimization for Travelling Salesman Problem via Deep Reinforcement Learning,
    Qi Li, Zhiguang Cao, Yining Ma, Yaoxin Wu, and Yue-Jiao Gong.
    ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2025. [Code&Paper] (Accept)

  2. [L2Opt, VRP] An Efficient Diffusion-based Non-Autoregressive Solver for Traveling Salesman Problem,
    Mingzhao Wang, You Zhou, Zhiguang Cao, Yubin Xiao, and Yuan Jiang.
    ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2025. [Code&Paper] (Accept)

  3. [L2Opt, COP] ReEvo: Large Language Models as Hyper-heuristics with Reflective Evolution,
    Haoran Ye, Jiarui, Wang, Zhiguang Cao, Jinkyoo Park, and Guojie Song.
    Advances in Neural Information Processing Systems (NeurIPS), 2024. [Code&Paper] (Accept)

  4. [L2Opt, VRP] Learning to Handle Complex Constraints for Vehicle Routing Problems,
    Jieyi Bi, Yining Ma, Jianan Zhou, Wen Song, Zhiguang Cao, Yaoxin Wu, and Jie Zhang.
    Advances in Neural Information Processing Systems (NeurIPS), 2024. [Code&Paper] (Accept)

  5. [L2Opt, VRP] Collaboration! Towards Robust Neural Methods for Routing Problems,
    Jianan Zhou, Yaoxin Wu, Zhiguang Cao, Wen Song, Jie Zhang, and Zhiqi Shen.
    Advances in Neural Information Processing Systems (NeurIPS), 2024. [Code&Paper] (Accept)

  6. [L2Opt, VRP] Hierarchical Neural Constructive Solver for Real-world TSP Scenarios,
    Yong Liang Goh, Zhiguang Cao, Yining Ma, Yanfei Dong, Mohammed Haroon Dupty, and Wee Sun Lee.
    ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2024. [Code&Paper]

  7. [L2Opt, VRP] MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts,
    Jianan Zhou, Zhiguang Cao, Yaoxin Wu, Wen Song, Yining Ma, and Jie Zhang.
    International Conference on Machine Learning (ICML), 2024. [Code&Paper]

  8. [L2Opt, CG] Adaptive Stabilization Based on Machine Learning for Column Generation,
    Yunzhuang Shen, Yuan Sun, Xiaodong Li, Zhiguang Cao, and Guangquan Zhang.
    International Conference on Machine Learning (ICML), 2024. [Code&Paper]

  9. [L2Opt, JSSP] Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem,
    Cong Zhang, Zhiguang Cao, Yaoxin Wu, Wen Song, and Jing Sun.
    The Conference on Uncertainty in Artificial Intelligence (UAI), 2024. [Code&Paper] (Accept)

  10. [L2Opt, VRP] Cross-Problem Learning for Solving Vehicle Routing Problems,
    Zhuoyi Lin, Yaoxin Wu, Zhiguang Cao, Wen Song, and Senthilnath Jayavelu.
    33rd International Joint Conference on Artificial Intelligence (IJCAI), 2024. [Code&Paper] (Accept)

  11. [L2Opt, JSSP] Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling,
    Cong Zhang, Zhiguang Cao, Wen Song, Yaoxin Wu, and Jie Zhang.
    International Conference on Learning Representations (ICLR), 2024. [Code&Paper]

  12. [L2Opt, VRP] GLOP: Learning Global Partition and Local Construction for Solving Large-scale Routing Problems in Real Time,
    Haoran Ye, Jiarui Wang, Helan Liang, Zhiguang Cao, Yong Li, and Fanzhang Li.
    38th AAAI Conference on Artificial Intelligence (AAAI), 2024. [Code&Paper]

  13. [L2Opt, MOCOP] Collaborative Deep Reinforcement Learning for Solving Multi-Objective Vehicle Routing Problems,
    Yaoxin Wu, Mingfeng Fan, Zhiguang Cao, Ruobin Gao, Yaqing Hou, and Guillaume Sartoretti.
    23rd International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2024. [Code&Paper]

  14. [L2Opt, VRP] Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt,
    Yining Ma, Zhiguang Cao, and Yeow Meng Chee.
    Advances in Neural Information Processing Systems (NeurIPS), 2023. [Code&Paper]

  15. [L2Opt, VRP] Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift,
    Yuan Jiang, Zhiguang Cao, Yaoxin Wu, Wen Song, and Jie Zhang.
    Advances in Neural Information Processing Systems (NeurIPS), 2023. [Code&Paper]

  16. [L2Opt, ACO] DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization,
    Haoran Ye, Jiarui Wang, Zhiguang Cao, Helan Liang, and Yong Li.
    Advances in Neural Information Processing Systems (NeurIPS), 2023. [Code&Paper]

  17. [L2Opt, MOCOP] Neural Multi-Objective Combinatorial Optimization with Diversity Enhancement,
    Jinbiao Chen, Zizhen Zhang, Zhiguang Cao, Yaoxin Wu, Yining Ma, Te Ye, and Jiahai Wang.
    Advances in Neural Information Processing Systems (NeurIPS), 2023. [Code&Paper]

  18. [L2Opt, MOCOP] Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization,
    Jinbiao Chen, Jiahai Wang, Zizhen Zhang, Zhiguang Cao, Te Ye, and Siyuan Chen
    Advances in Neural Information Processing Systems (NeurIPS), 2023. [Code&Paper]

  19. [L2Opt, BBO] MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning,
    Zeyuan Ma, Hongshu Guo, Jiacheng Chen, Zhenrui Li, Guojun Peng, Yue-Jiao Gong, Yining Ma, Zhiguang Cao.
    Advances in Neural Information Processing Systems (NeurIPS), 2023. [Code&Paper]

  20. [L2Opt, VRP] Towards Omni-generalizable Neural Methods for Vehicle Routing Problems,
    Jianan Zhou, Yaoxin Wu, Wen Song, Zhiguang Cao, and Jie Zhang.
    International Conference on Machine Learning (ICML), 2023. [Code&Paper]

  21. [L2Opt, VRP] Multi-View Graph Contrastive Learning for Solving Vehicle Routing Problems,
    Yuan Jiang, Zhiguang Cao, Yaoxin Wu, and Jie Zhang.
    The Conference on Uncertainty in Artificial Intelligence (UAI), 2023. [Code&Paper]

  22. [L2Opt, VRP] Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation,
    Jieyi Bi, Yining Ma, Jiahai Wang*, Zhiguang Cao*, Jinbiao Chen, Yuan Sun, and Yeow Meng Chee.
    Advances in Neural Information Processing Systems (NeurIPS), 2022. [Code&Paper]

  23. [L2Opt, MOIP] Graph Learning Assisted Multi-Objective Integer Programming,
    Yaoxin Wu, Wen Song, Zhiguang Cao*, Jie Zhang, Abhishek Gupta, and Mingyan Simon Lin.
    Advances in Neural Information Processing Systems (NeurIPS), 2022. [Code&Paper]

  24. [L2Opt, VRP] Efficient Neural Neighbourhood Search for Pickup and Delivery Problems,
    Yining Ma, Jingwen Li, Zhiguang Cao*, Wen Song, Hongliang Guo, Yue-Jiao Gong, and Yeow Meng Chee.
    31st International Joint Conference on Artificial Intelligence (IJCAI), pp. 4776-4784, 2022. [Code&Paper]

  25. Interpreting Trajectories from Multiple Views: A Hierarchical Self-Attention Network for Estimating the Time of Arrival,
    Zebin Chen, Xiaolin Xiao, Yue-Jiao Gong, Jun Fang, Nan Ma, Hua Chai, Zhiguang Cao.
    ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2022. [Code&Paper]

  26. [L2Opt, SIP] Learning Scenario Representation for Solving Two-stage Stochastic Integer Programs,
    Yaoxin Wu, Wen Song, Zhiguang Cao*, and Jie Zhang.
    International Conference on Learning Representations (ICLR), 2022. [Code&Paper]

  27. [L2Opt, VRP] Learning to Solve Routing Problems via Distributionally Robust Optimization,
    Yuan Jiang, Yaoxin Wu, Zhiguang Cao*, and Jie Zhang.
    36th AAAI Conference on Artificial Intelligence (AAAI), 2022. [Code&Paper]

  28. [L2Opt, VRP] Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer,
    Yining Ma, Jingwen Li, Zhiguang Cao*, Wen Song*, Le Zhang, Zhenghua Chen, and Jing Tang.
    Advances in Neural Information Processing Systems (NeurIPS), pp. 11096-11107, 2021. [Code&Paper]

  29. [L2Opt, VRP] NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem,
    Liang Xin, Wen Song, Zhiguang Cao*, and Jie Zhang.
    Advances in Neural Information Processing Systems (NeurIPS), pp. 7472-7483, 2021. [Code&Paper]

  30. [L2Opt, IP] Learning Large Neighborhood Search Policy for Integer Programming,
    Yaoxin Wu, Wen Song, Zhiguang Cao, and Jie Zhang.
    Advances in Neural Information Processing Systems (NeurIPS), pp. 30075-30087, 2021. [Code&Paper]

  31. [L2Opt, VRP] Multi-Decoder Attention Model with Embedding Glimpse for Solving Vehicle Routing Problems,
    Liang Xin, Wen Song, Zhiguang Cao*, and Jie Zhang.
    35th AAAI Conference on Artificial Intelligence (AAAI), pp. 12042-12049, 2021. [Code&Paper]

  32. [L2Opt, BPP] Solving 3D Bin Packing Problem via Multimodal Deep Reinforcement Learning,
    Yuan Jiang, Zhiguang Cao*, and Jie Zhang.
    20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1548-1550, 2021. (Extended Abstract) [Link]

  33. [L2Opt, JSSP] Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning,
    Cong Zhang, Wen Song, Zhiguang Cao*, Jie Zhang, Puay Siew Tan, Chi Xu.
    Advances in Neural Information Processing Systems (NeurIPS), pp. 1621-1632, 2020. [Code&Paper]

  34. AATEAM: Achieving the Ad Hoc Teamwork by Employing the Attention Mechanism,
    Shuo Chen, Ewa Andrejczuk, Zhiguang Cao, Jie Zhang.
    34th AAAI Conference on Artificial Intelligence (AAAI), pp. 7095-7102, 2020. [Link]

  35. [L2Opt, SSP] Maximizing the Probability of Arriving on Time: A Practical Q-Learning Method,
    Zhiguang Cao, Hongliang Guo, Jie Zhang, Frans Oliehoek and Ulrich Fastenrath.
    31st AAAI Conference on Artificial Intelligence (AAAI), pp. 4481-4487, 2017. [Link]

  36. Multiagent-based Route Guidance for Increasing the Chance of Arrival on Time,
    Zhiguang Cao, Hongliang Guo, Jie Zhang, and Ulrich Fastenrath.
    30th AAAI Conference on Artificial Intelligence (AAAI), pp. 3814-3820, 2016. [Link]

Journal Articles

  1. [L2Opt, VRP] Efficient Neural Collaborative Search for Pickup and Delivery Problems,
    Detian Kong, Yining Ma, Zhiguang Cao, Tianshu Yu, and Jianhua Xiao.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2024. [Code&Paper]

  2. [L2Opt, VRP] Deep Reinforcement Learning for Solving Vehicle Routing Problems with Backhauls,
    Conghui Wang, Zhiguang Cao, Yaoxin Wu, Long Teng, and Guohua Wu.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024. [Code&Paper]

  3. [L2Opt, MOCOP] Conditional Neural Heuristic for Multi-objective Vehicle Routing Problems,
    Mingfeng Fan, Yaoxin Wu, Zhiguang Cao, Wen Song, Guillaume Sartoretti, Huan Liu, and Guohua Wu.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024. [Code&Paper]

  4. [L2Opt, HyperHeuristic] Deep Reinforcement Learning for Dynamic Algorithm Selection: A Proof-of-Principle Study on Differential Evolution,
    Hongshu Guo, Yining Ma, Zhiguang Cao, Yue-Jiao Gong, and Jun Zhang.
    IEEE Transactions on Systems, Man and Cybernetics: Systems (SMCA), 2024. [Code&Paper]

  5. [L2Opt, UAV] DL-DRL: A double-layer deep reinforcement learning approach for large-scale task scheduling of multi-UAV,
    Xiao Mao, Guohua Wu, Mingfeng Fan, Zhiguang Cao, and Witold Pedrycz.
    IEEE Transactions on Automation Science and Engineering (T-ASE), 2024. [Code&Paper]

  6. [L2Opt, SSP] SEGAC: Sample Efficient Generalized Actor Critic for the Stochastic On-Time Arrival Problem,
    Hongliang Guo, Zhi He, Wenda Sheng, Zhiguang Cao, Yingjie Zhou and Weinan Gao.
    IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2024. [Code&Paper]

  7. [L2Opt, EC] Island-Based Evolutionary Computation with Diverse Surrogates and Adaptive Knowledge Transfer for High-Dimensional Data-Driven Optimization,
    Xian-Rong Zhang, Yue-Jiao Gong, Zhiguang Cao, and Jun Zhang.
    ACM Transactions on Evolutionary Learning and Optimization (TELO), 2024. [Code&Paper]

  8. The low-carbon vehicle routing problem with dynamic speed on steep roads,
    Jianhua Xiao, Xiaoyang Liu, Huixian Zhang, Zhiguang Cao, Liujiang Kang and Yunyun Niu.
    Computers & Operations Research (CAOR), 2024. [Code&Paper]

  9. [L2Opt, VRP] Learning Feature Embedding Refiner for Solving Vehicle Routing Problems,
    Jingwen Li, Yining Ma, Zhiguang Cao, Yaoxin Wu, Wen Song, Jie Zhang, and Yeow Meng Chee.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023. [Code&Paper]

  10. [L2Opt, VRP] Learning Large Neighborhood Search for Vehicle Routing in Airport Ground Handling,
    Jianan Zhou, Yaoxin Wu, Zhiguang Cao, Wen Song, Jie Zhang, and Zhenghua Chen.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023. [Code&Paper]

  11. [L2Opt, VRP] Neural Airport Ground Handling,
    Yaoxin Wu, Jianan Zhou, Yunwen Xia, Xianli Zhang, Zhiguang Cao, and Jie Zhang.
    IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2023. [Code&Paper]

  12. [L2Opt, Planning] DRL-Searcher: A Unified Approach to Multi-Robot Efficient Search for a Moving Target,
    Hongliang Guo, Qihang Peng, Zhiguang Cao, and Yaochu Jin.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023. [Code&Paper]

  13. [L2Opt, Scheduling] Stochastic Economic Lot Scheduling via Deep Reinforcement Learning,
    Wen Song, Nan Mi, Qiqiang Li, Jing Zhuang, and Zhiguang Cao.
    IEEE Transactions on Automation Science and Engineering (TASE), 2023. [Code&Paper]

  14. [L2Opt, AC] Instance-Specific Algorithm Configuration via Unsupervised Deep Graph Clustering,
    Wen Song, Yi Liu, Zhiguang Cao, Yaoxin Wu, and Qiqiang Li.
    Engineering Applications of Artificial Intelligence (EAAI), 2023. [Code&Paper]

  15. Cooperative Trucks and Drones for Rural Last-Mile Delivery with Steep Roads,
    Jiuhong Xiao, Ying Li, Zhiguang Cao, and Jianhua Xiao.
    Computers & Industrial Engineering (CAIE), 2023.

  16. [L2Opt, Survey] A Review on Learning to Solve Combinatorial Optimization Problems in Manufacturing,
    Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song, Le Zhang, Zhiguang Cao, and Jie Zhang.
    IET Collaborative Intelligent Manufacturing (CIM), 2022. [Paper]

  17. [L2Opt, VRP] Learning to Solve Multiple-TSP with Time Window and Rejection via Deep Reinforcement Learning,
    Rongkai Zhang, Cong Zhang, Zhiguang Cao, Wen Song, Puay Siew Tan, Jie Zhang, Bihan Wen, and Justin Dauwels.
    IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2022. [Code&Paper]

  18. [L2Opt, JSSP] Flexible Job Shop Scheduling via Graph Neural Network and Deep Reinforcement Learning,
    Wen Song, Xinyang Chen, Qiqiang Li, and Zhiguang Cao.
    IEEE Transactions on Industrial Informatics (TII), vol. 19, no. 2, pp. 1600-1610, 2022. [Code&Paper]

  19. [L2Opt, UAV] Deep Reinforcement Learning for UAV Routing in the Presence of Multiple Charging Stations,
    Mingfeng Fan, Yaoxin Wu, Tianjun Liao, Zhiguang Cao, Hongliaing Guo, Guillaume Sartoretti, and Guohua Wu.
    IEEE Transactions on Vehicular Technology (TVT), 2022. [Code&Paper]

  20. [L2Opt, VRP] Deep Reinforcement Learning for Solving the Heterogeneous Capacitated Vehicle Routing Problem,
    Jingwen Li, Yining Ma, Ruize Gao, Zhiguang Cao*, Andrew Lim, Wen Song, and Jie Zhang.
    IEEE Transactions on Cybernetics (T-Cybernetics), vol. 52, no. 12, pp. 13572-13585 2021. [Code&Paper]

  21. [L2Opt, VRP] Learning Improvement Heuristics for Solving Routing Problems,
    Yaoxin Wu, Wen Song*, Zhiguang Cao*, Jie Zhang, and Andrew Lim.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 33, no. 9, pp. 5057-5069, 2021. [Code&Paper]

  22. [L2Opt, VRP] Heterogeneous Attentions for Solving Pickup and Delivery Problem via Deep Reinforcement Learning,
    Jingwen Li, Liang Xin, Zhiguang Cao*, Andrew Lim, Wen Song, and Jie Zhang.
    IEEE Transactions on Intelligent Transportation Systems (T-ITS), vol. 23, no. 3, pp. 2306-2315, 2021. [Code&Paper]

  23. [L2Opt, BPP] Learning to Solve 3-D Bin Packing Problem via Deep Reinforcement Learning and Constraint Programming,
    Yuan Jiang, Zhiguang Cao*, and Jie Zhang.
    IEEE Transactions on Cybernetics (T-Cybernetics), 2021. [Link]

  24. [L2Opt, CSP] Learning Variable Ordering Heuristics for Solving Constraint Satisfaction Problems,
    Wen Song, Zhiguang Cao*, Jie Zhang, Chi Xu, and Andrew Lim.
    Engineering Applications of Artificial Intelligence (EAAI), 2021. [Code&Paper]

  25. [L2Opt, SSP] GP3: Gaussian Process Path Planning for Reliable Shortest Path in Transportation Networks,
    Hongliang Guo, Xuejie Hou, Zhiguang Cao*, and Jie Zhang.
    IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2021. [Link]

  26. First Train Timetabling and Bus Service Bridging in Intermodal Bus-and-Train Transit Networks,
    Liujiang Kang, Hao Li, Huijun Sun, Jianjun Wu, Zhiguang Cao, and Nsabimana Buhigiro.
    Transportation Research Part B: Methodological (TRB), vol. 149, pp. 443-462, 2021. [Link]

  27. [L2Opt, VRP] Step-wise Deep Learning Models for Solving Routing Problems,
    Liang Xin, Wen Song, Zhiguang Cao, and Jie Zhang.
    IEEE Transactions on Industrial Informatics (TII), vol. 17, no. 7, pp. 4861-4871, 2020. [Code&Paper]

  28. [L2Opt, SSP] Using Reinforcement Learning to Minimize the Probability of Delay Occurrence in Transportation,
    Zhiguang Cao, Hongliang Guo, Wen Song, Kaizhou Gao, and Zhenghua Chen.
    IEEE Transactions on Vehicular Technology (TVT), vol. 69, no. 3, pp. 2424-2436, 2020. [Link]

Patents

  • Fahrrouten für Landfahrzeuge (A Method for determining routes for road vehicles),
    Ulrich Fastenrath, Jie Zhang, Zhiguang Cao, Hongliang Guo. DE 10 2016 220 561 A1, 2018.04.26. (German)

  • Verfahren zur kooperativen Berechnung von Fahrrouten für Landfahrzeuge (A Method For Cooperative Calculation of Travel Routes for Land Vehicles),
    Ulrich Fastenrath, Zhiguang Cao, Hongliang Guo, Dusit Niyato, Jie Zhang. DE 10 2015 223 824 A1, 2017.06.01. (German)

  • Verfahren zur Berechnung einer Route fur ein Landfahrzeug (A Method For Calculating A Route For A Land Vehicle),
    Ulrich Fastenrath, Zhiguang Cao, Dusit Niyato, Hongliang Guo, Jie Zhang. DE 10 2015 205 901 A1, 2016.10.06. (German)