Liu Shengcai


Research Area
  • Learning to Optimise
  • Combinatorial Optimisation
  • Black-box Optimisation


1. Shengcai Liu, Yu Zhang, Ke Tang, and Xin Yao. How Good Is Neural Combinatorial Optimisation? A Systematic Evaluation on the Travelling Salesman Problem. IEEE Computational Intelligence Magazine, 18(3): 14-28. (2023)

2. Zeyu Dai, Shengcai Liu*, Qing Li, and Ke Tang. Saliency Attack: Towards Imperceptible Black-box Adversarial Attack. ACM Transactions on Intelligent Systems and Technology, 14(3): 1-20. (corresponding author) (2023)

3. Rui He, Shengcai Liu*, Shan He, and Ke Tang. Multi-Domain Active Learning: Literature Review and Comparative Study. IEEE Transactions on Emerging Topics in Computational Intelligence, 7(3): 791-804. (corresponding author) (2023)

4. Rui He, Shengcai Liu*, Jiahao Wu, Shan He, and Ke Tang. Multi-Domain Learning from Insufficient Annotations. In: Proceedings of the 26th European Conference on Artificial Intelligence (ECAI’2023), Kraków, Poland, 2023, To appear. (corresponding author) (2023)

5. Shengcai Liu, Fu Peng, and Ke Tang. Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles. In: Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI’2023), Washington, DC, 8852-8860. (2023)

6. Shengcai Liu, Peng Yang, and Ke Tang. Approximately Optimal Construction of Parallel Algorithm Portfolios by Evolutionary Intelligence (in Chinese). SCIENTIA SINICA Technologica, 53(2): 280-290. (2023)

7. Shengcai Liu, Ning Lu, Cheng Chen, and Ke Tang. Efficient Combinatorial Optimisation for Word-level Adversarial Textual Attack. IEEE/ACM Transactions on Audio, Speech and Language Processing, 30: 98-111. (2022)

8. Shengcai Liu, Ke Tang, and Xin Yao. Generative Adversarial Construction of Parallel Portfolios. IEEE Transactions on Cybernetics, 52(2): 784-795. (2022)

9. Fu Peng, Shengcai Liu*, and Ke Tang. Training Quantised Deep Neural Networks via Cooperative Coevolution. In: Proceedings of the 13th International Conference on Swarm Intelligence (ICSI’2022), Xi'an, China, 81-93. (corresponding author) (2022)

10. Shengcai Liu, Ke Tang, Peng Yang, and Xin Yao. Few-shots Parallel Algorithm Portfolio Construction via Co-evolution. IEEE Transactions on Evolutionary Computation, 25(3): 595-607. (2021)

11. Shengcai Liu, Ke Tang, and Xin Yao. Memetic Search for Vehicle Routing with Simultaneous Pickup-Delivery and Time Windows. Swarm and Evolutionary Computation, 66: 100927. (2021)

12. Kangfei Zhao, Shengcai Liu*, Yu Rong, and Jeffrey Xu Yu. Towards Feature-free TSP Solver Selection: A Deep Learning Approach. In: Proceedings of the 20th International Joint Conference on Neural Networks (IJCNN’2021), Virtual Event, 1-8. (corresponding author) (2021)

13. Shengcai Liu, Ke Tang, and Xin Yao. On Performance Estimation in Automatic Algorithm Configuration. In: Proceedings of The 34th AAAI Conference on Artificial Intelligence (AAAI’2020), New York, NY, 2384-2391. (2020)

14. Shengcai Liu, Ke Tang, and Xin Yao. Automatic Construction of Parallel Portfolios via Explicit Instance Grouping. In: Proceedings of The 33rd AAAI Conference on Artificial Intelligence (AAAI’2019), Honululu, HI, 1560-1567. (2019)

Research Services

  • Program Committee Member: AAAI (2020-2023), IJCAI (2020-2023), CEC (2021-2023)
  • Journal Reviewer: TPAMI, TEVC, TCYB, CIM, TNNLS, JAIR,  SWEVO, Memetic Computing, Natural Computing