演化计算，多目标优化与学习，大规模优化

W Hong, G Li, S Liu, P Yang, K Tang, “Multi-Objective Evolutionary Optimization For Hardware-Aware Neural Network Pruning,” Fundamental Research, in press.

H Shang, J-L Wu, W Hong, C Qian. Neural Network Pruning by Cooperative Coevolution. IJCAI 2022: 4814-4820

J-L Wu, H Shang, W Hong, C Qian. Robust Neural Network Pruning by Cooperative Coevolution. PPSN (1) 2022: 459-473

Z Wang, B Mao, H Hao, W Hong, C Xiao, A Zhou, “Enhancing Diversity by Local Subset Selection in Evolutionary Multiobjective Optimization,” IEEE Transactions on Evolutionary Computation, in press.

W Chen, W Hong, H Zhang, P Yang, K Tang, “Multi-Fidelity Simulation Modeling for Discrete Event Simulation: An Optimization Perspective,” IEEE Transactions on Automation Science and Engineering, in press.

W Hong, P Yang, and K Tang, “Evolutionary Computation for Large-Scale Multi-Objective Optimization: A Decade of Progresses,” International Journal of Automation and Computing, 2021, 18: 155–169.

W Hong, C Qian, and K Tang, “Efficient Minimum Cost Seed Selection with Theoretical Guarantees for Competitive Influence Maximization,” IEEE Transactions on Cybernetics, 2021, 51(12): 6091-6104.

W Hong, P Yang, Y Wang, and K Tang, “Multi-objective Magnitude-Based Pruning for Latency-Aware Deep Neural Network Compression,” PPSN 2020: 470-483.

W Hong, K Tang, A Zhou, H Ishibuchi and X Yao, “A Scalable Indicator-Based Evolutionary Algorithm for Large-Scale Multiobjective Optimization,” IEEE Transactions on Evolutionary Computation, 2019, 23(3): 525-537.

W Hong and L Chen, “Thermo-Economic Multi-Objective Optimization of Adiabatic Compressed Air Energy Storage (A-CAES) System,” ICCAI 2018: 132-138.

W Hong and K Tang, “Convex Hull-Based Multiobjective Evolutionary Computation For Maximizing Receiver Operating Characteristics Performance,” Memetic Computing, 2016, 8(1): 35-44.

W Hong, G Lu, P Yang, Y Wang, and K Tang, “A New Evolutionary Multi-Objective Algorithm for Convex Hull Maximization,” CEC 2015: 931-938.