代表性论著20篇 [1]K. J. Qiao, G. Liu, J. Liang*, Y. J. Wang*, L. Li, K. J. Yu, C. T. Yue. A level-based multi-population self-adaptive constrained multiobjective evolutionary algorithm for cascade reservoir scheduling [J]. IEEE Transactions on Evolutionary Computation, 2026, DOI: 10.1109/TEVC.2026.3651698. [2]K. J. Qiao, J. Liang*, D. W. Gong*, Y. Zhang, C. Y. Dai, J. Ma, X. X. Ban, K. J. Yu. A time-division based constrained multiobjective optimization method for coal mine integrated energy system dispatch problem [J]. IEEE Transactions on Cybernetics, 2026, 56(5): 2991-3004. [3]X. Y. Zhou, W. F. Lin, K. J. Yu, K. J. Qiao*. Dynamic escaping population driven evolutionary algorithm for multi-objective optimization problems with deceptive constraints [J]. IEEE Transactions on Evolutionary Computation, 2026, DOI: 10.1109/TEVC.2026.3697492. [4]K. J. Yu, Z. Y. Yang, J. Liang, K. J. Qiao*, B. Y. Qu, Qiao Peng, P. N. Suganthan. Large-scale constrained multiobjective optimization based on variable adaptive optimization and population reconstruction [J]. IEEE Transactions on Emerging Topics in Computational Intelligence, 2026, 10(2): 1625-1640. [5]K. J. Qiao, J. Liang*, W. F. Guo*, Z. Hu, K. J. Yu, P. N. Suganthan. Constrained multi-objective optimization-based temporal network observability for biomarker identification of individual patients [J]. IEEE Journal of Biomedical and Health Informatics, 2026, 30(5): 3630-3642. [6]K. J. Yu, L. H. Duan, J. Liang, K. J. Qiao*, B. Y. Qu, Q. Sui, X. Y. Ren. A cooperation and competition-based tri-population evolutionary algorithm for constrained multi-objective optimization [J]. Applied Soft Computing, 2025, 183: 113658. [7]K. J. Yu, Z. Y. Yang, J. Liang, K. J. Qiao*, B. Y. Qu, P. N. Suganthan. An individual adaptive evolution and regional collaboration based evolutionary algorithm for large-scale constrained multiobjective optimization problems [J]. Swarm and Evolutionary Computation, 2025, 95: 101925. [8]K. J. Qiao, J. Liang*, K. J. Yu, C. T. Yue, H. Y. Lin, D. Z. Zhang, B. Y. Qu. Evolutionary constrained multiobjective optimization: scalable high-dimensional constraint benchmarks and algorithm [J]. IEEE Transactions on Evolutionary Computation, 2024, 28(4): 965-979.【ESI高被引】 [9]K. J. Qiao, K. J. Yu, C. T. Yue, B. Y. Qu, M. N. Liu, J. Liang*. A cooperative multi-step mutation strategy for multi-objective optimization problems with deceptive constraints [J]. IEEE Transactions on Systems, Man and Cybernetics: Systems, 2024, 54(11): 6670-6682. [10]K. J. Qiao, J. Liang*, K. J. Yu, X. X. Ban, C. T. Yue, B. Y. Qu, P. N. Suganthan. Constraints separation based evolutionary multitasking for constrained multi-objective optimization problems [J]. IEEE/CAA Journal of Automatica Sinica, 2024, 11(8): 1819-1835. [11]K. J. Qiao, J. Liang*, W. F. Guo*, Z. Hu, K. J. Yu, P. N. Suganthan. Knowledge-embedded constrained multiobjective evolutionary algorithm based on structural network control principles for personalized drug targets recognition in cancer [J]. Information Sciences, 2024, 679: 121033. [12]K. J. Qiao, J. Liang*, K. J. Yu, W. F. Guo, C. T. Yue, B. Y. Qu, P. N. Suganthan. Benchmark problems for large-scale constrained multi-objective optimization with baseline results [J]. Swarm and Evolutionary Computation, 2024, 86: 101504.【ESI高被引】 [13]K. J. Qiao, Z. L. Chen, B. Y. Qu, K. J. Yu, C. T. Yue, K. Chen, J. Liang*. A dual-population evolutionary algorithm based on dynamic constraint processing and resources allocation for constrained multi-objective optimization problems [J]. Expert Systems with Applications, 2024, 238: 121707. [14]K. J. Qiao, J. Liang*, K. J. Yu, M. H. Wang, B. Y. Qu, C. T. Yue, Y. N. Guo. A self-adaptive evolutionary multi-task based constrained multi-objective evolutionary algorithm [J]. IEEE Transactions on Emerging Topics in Computational Intelligence, 2023, 7(4): 1098-1112.【ESI高被引】 [15]K. J. Qiao, K. J. Yu, B. Y. Qu, J. J. Liang*, H. Song, C. T. Yue, H. Y. Lin, K. C. Tan. Dynamic auxiliary task-based evolutionary multitasking for constrained multi-objective optimization [J]. IEEE Transactions on Evolutionary Computation, 2023, 27(3): 642-656.【ESI高被引】 [16]K. J. Qiao, J. Liang*, Z. Y. Liu, K. J. Yu, C. T. Yue, B. Y. Qu. Evolutionary multitasking with global and local auxiliary tasks for constrained multi-objective optimization [J]. IEEE/CAA Journal of Automatica Sinica, 2023, 10(10): 1951-1964.【ESI高被引】 [17]K. J. Qiao, K. J. Yu, B. Y. Qu, J. J. Liang*, C. T. Yue, X. X. Ban. Feature extraction for recommendation of constrained multi-objective evolutionary algorithms [J]. IEEE Transactions on Evolutionary Computation, 2023, 27(4): 979-993. [18]K. J. Qiao, K. J. Yu, B. Y. Qu, J. Liang*, H. Song, C. T. Yue. An evolutionary multitasking optimization framework for constrained multi-objective optimization problems [J]. IEEE Transactions on Evolutionary Computation, 2022, 26(2): 263-277.【ESI高被引】 [19]K. J. Qiao, J. Liang, K. J. Yu*, M. H. Yuan, B. Y. Qu, C. T. Yue. Self-adaptive resources allocation-based differential evolution for constrained evolutionary optimization [J]. Knowledge-Based Systems, 2022, 235: 107653-107667. [20]K. J. Qiao, J. Liang*, B. Y. Qu, K. J. Yu, C. T. Yue, H. Song. Differential evolution with level-based learning mechanism [J]. Complex System Modeling and Simulation, 2022, 2(1): 35-58. |
