期刊论文

  1. Chaoli Sun, Xiaojun Wang, Junwei Ma, Gang Xie, A Composition–decomposition Based Federated Learning,  Complex & Intelligent Systems, 2023, accepted. ( https://doi.org/10.1007/s40747-023-01198-x)
  2. Shufen Qin, Chaoli Sun, Qiqi Liu, Yaochu Jin, A Performance Indicator Based Infill Criterion for Expensive Multi-/Many-objective Optimization, IEEE Transactions on Evolutionary Computation, 2023, accepted.
  3. Hao Wang, Chaoli Sun, Gang Xie, Xiao-Zhi Gao, Farooq Akhtar, A performance approximation assisted expensive many-objective evolutionary algorithm, Information Sciences, 2023, 625, 20-35.
  4. 张国晨,刘鹏飞,孙超利,一种新环境选择策略的多模态多目标优化算法, 应用科学学报,2022,40(05):739-748.
  5. 张国晨,崔钧皓,王浩,孙超利,李春鹏,自适应模型选用辅助的多种群进化算法, 小型微型计算机系统，2022，录用.
  6. Hao Wang, Chaoli Sun, Haibo Yu, Xiaobo Li, A decomposition-based many-objective evolutionary algorithm with optional performance indicators, Complex & Intelligent Systems, 2022: 1-20.
  7. Mai Sun, Chaoli Sun, Xiaobo Li, Guochen Zhang, Farooq Akhtar, Surrogate Ensemble Assisted large-scale Expensive Optimization with Random Grouping, Information Sciences, 2022, 615, 226-237.
  8. 王浩，孙超利，张国晨，基于估值不确定度排序顺序均值采样的昂贵高维多目标进化算法, 控制与决策，2022，录用.
  9. Mai Sun, Chaoli Sun, Guochen Zhang, Large-scale Expensive Optimization with a Switching Strategy, Complex System Modeling and Simulation, 2022, 2(3), 253-263.
  10. Shufen Qin, Chan Li, Chaoli Sun, Guochen Zhang, Xiaobo Li, Multiple Infill Criteria Assisted Hybrid Evolutionary Optimization for Medium-dimensional Computationally Expensive Problems, Complex & Intelligent Systems, 2022, 8(1), 583-595.
  11. 乔刚柱，王瑞，孙超利，基于分解的高维多目标改进进化算法，计算机应用，2021, 41(11), 3097-3103.
  12. 孙超利，李贞，金耀初，模型辅助的计算费时进化高维多目标优化，自动化学报，2022, 48(04), 1119-1128.
  13. 孙超利，李婵，秦淑芬，张国晨，李晓波，基于不确定度采样准则的费时问题优化算法，控制与决策，2022, 37(06), 1541-1549.
  14. 于成龙，付国霞，孙超利，张国晨，全局/局部模型交替优化辅助的差分进化算法，计算机工程，2022, 48(03), 115-123.
  15. Shufen Qin, Chaoli Sun, Yaochu Jin, Ying Tan, Jonathan Fieldsend, Large-scale Evolutionary Multi-objective Optimization Assisted by Directed Sampling, IEEE Transactions on Evolutionary Computation, 2021, 25(4), 724-738.
  16. Zhihai Ren, Chaoli Sun, Ying Tan, Guochen Zhang, Shufen Qin, A Bi-stage Surrogate-assisted Hybrid Algorithm for Expensive Optimization Problems, C omplex & Intelligent Systems, 2021, 7, 1391-1405.
  17. Hao Wang, Chaoli Sun, Guochen Zhang, Jonathan E. Fieldsend, Yaochu Jin, Non-dominated Sorting on Performance Indicators for Evolutionary Many-objective Optimization, Information Sciences, 2021, 551, 23-38.
  18. Yi Zhao, Chaoli Sun, Jianchao Zeng, Ying Tan, Guochen Zhang, A Surrogate-ensemble Assisted Expensive Many-objective Optimization, Knowledge-Based Systems, 2021, 211, 106520.
  19. Peng Liao, Chaoli Sun, Guochen Zhang, Yaochu Jin, Multi-surrogate Multi-tasking Optimization of Expensive problems, Knowledge-Based Systems, 2020, 205, 106262.
  20. Hao Wang, Mengnan Liang, Chaoli Sun, Guochen Zhang, Liping Xie, Multiple-strategy learning particle swarm optimization for large-scale optimization problems, Complex & Intelligent Systems, 2021, 7(1), 1-16.
  21. Shufen Qin, Chaoli Sun, Guochen Zhang, Xiaojuan He, Ying Tan, A modified particle swarm optimization based on decomposition with different ideal points for many-objective optimization problems, Complex & Intelligent Systems, 2020, 6(2), 263-274.
  22. 田杰，孙超利，谭瑛，曾建潮，基于多点加点准则的代理模型辅助社会学习微粒群算法，控制与决策，2020，35(1)，131-138.
  23. Jie Tian, Ying Tan, Jianchao Zeng, Chaoli Sun, Yaochu Jin, Multi-objective Infill Criterion Driven Gaussian Process Assisted Particle Swarm Optimization of High-dimensional Expensive Problems, IEEE Transactions on Evolutionary Computation, 2019, 23(3), 459-472.
  24. Haibo Yu, Ying Tan, Jianchao Zeng, Chaoli Sun, A generation-based optimal restart strategy for surrogate-assisted social learning particle swarm optimization, Knowledge-Based Systems, 2019, 163(1), pp. 14-25.
  25. Haibo Yu, Ying Tan, Chaoli Sun, Jianchao Zeng, A comparison of quality measures for model selection in surrogate assisted evolutionary algorithm, Soft Computing, 2019, 23(23), pp. 12417-12436.
  26. Handing Wang, Yaochu Jin, Chaoli Sun, John Doherty, Offline data-driven evolutionary optimization using selective surrogate ensembles, IEEE Transactions on Evolutionary Computation, 2018, 23(2), pp. 203-216.
  27. Haibo Yu, Ying Tan, Jianchao Zeng, Chaoli Sun, Yaochu Jin, Surrogate-assisted Hierarchical Particle Swarm Optimization, Information Sciences, 2018, 454-455, pp. 59-72.
  28. Chaoli Sun, Yaochu Jin, Jinliang Ding, Jianchao Zeng, A fitness approximation assisted competitive swarm optimizer for large scale expensive optimization problems, Memetic Computing, 2018, 10(2), pp. 123-134.
  29. Chaoli Sun, Yaochu Jin, Ran Cheng, Jinliang Ding, Jianchao Zeng, Surrogate-assisted Cooperative Swarm Optimization of High-dimensional Expensive Problems, IEEE Transactions on Evolutionary Computation, 2017, 21(4), 644-660.
  30. 孙超利，郭一娜，谭瑛，径向基函数神经网络辅助的微粒群算法，太原科技大学学报，2017, 38(3), pp. 178-184.
  31. Chaoli Sun, Yaochu Jin, Jianchao Zeng, Yang Yu, A Two-layer Surrogate-assisted Particle Swarm Optimization Algorithm, Soft Computing, 2015, 19(6), pp. 1461-1475.
  32. 刘彤，孙超利，曾建潮，微粒群进化估值策略在多目标优化中的应用，太原科技大学学报，2015, 36(5), pp. 338-347.
  33. Chaoli Sun, Jianchao Zeng, Jengshyang Pan, Songdong Xue, Yaochu Jin, A New Fitness Estimation Strategy for Particle Swarm Optimization, Information Sciences, 2013, 221, pp. 355-370.
  34. Chaoli Sun, Jianchao Zeng, Jengshyang Pan, A Modified Particle Swarm Optimization with Feasibility-based Rules for Mixed-variable Optimization Problems, International Journal of Innovative Computing, Information and Control, 2011, 7(6), 3081-3096.
  35. Chaoli Sun, Jianchao Zeng, Jengshyang Pan, An Improved Vector Particle Swarm Optimization for Constrained Optimization Problems, Information Sciences, 2011, 181(6), 1153-1163.
  36. Chaoli Sun, Ying Tan, Jianchao Zeng, Jengshyang Pan, Yuanfang Tao, The Structure Optimization of Main Beam for Bridge Crane Based on An Improved PSO, Journal of Computers, 2011, 6(8), 1585-1590.
  37. Chaoli Sun, Jianchao Zeng, Jengshyang Pan, Yuanfang Tao, Crank Block Steering Mechanism Optimization for Forklift Truck Based on Vector PSO, Advanced Materials Research, 2011, 145(43), 43-48.