Publications


[IEEE]

ESI Highly Cited Papers

  1. Zhi-Hui Zhan(詹志辉), J. Zhang, Y. Li, and H. Chung, “Adaptive particle swarm optimization,” IEEE Transactions on Systems, Man, and Cybernetics--Part B, vol. 39, no. 6, pp. 1362-1381, Dec. 2009.[PDF]【ESI Highly Cited Paper，ESI高被引论文，IEEE Trans. on SMC Part B和IEEE Trans. Cybernetics近25年来（1998年至今）刊印的共6600多篇论文中被引次数排名第2的论文】

  2. Zhi-Hui Zhan(詹志辉), J. Zhang, Y. Li, and Y. H. Shi, “Orthogonal learning particle swarm optimization,” IEEE Transactions on Evolutionary Computation, vol. 15, no. 6, pp. 832-847, Dec. 2011.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  3. Zhi-Hui Zhan(詹志辉), J. Li, J. Cao, J. Zhang, H. Chung, and Y. H. Shi, “Multiple populations for multiple objectives: A coevolutionary technique for solving multiobjective optimization problems,” IEEE Transactions on Cybernetics, vol. 43, no. 2, pp. 445-463, April. 2013.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  4. Z. J. Wang, J. R. Jian, Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Li, S. Kwong, and J. Zhang, “Gene targeting differential evolution: A simple and efficient method for large scale optimization,” IEEE Transactions on Evolutionary Computation, vol. 27, no. 4, pp. 964-979, Aug. 2023.[PDF][Share]【ESI Highly Cited Paper，ESI高被引论文】

  5. S. H. Wu(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. C. Tan, and J. Zhang, “Orthogonal transfer for multitask optimization,” IEEE Transactions on Evolutionary Computation, vol. 27, no. 1, pp. 185-200, Jan. 2023.[PDF-online][PDF][Share][Share2]【ESI Highly Cited Paper，ESI高被引论文】

  6. J. Y. Li(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. C. Tan, and J. Zhang, “A meta-knowledge transfer-based differential evolution for multitask optimization,” IEEE Transactions on Evolutionary Computation, vol. 26, no. 4, pp. 719-734, Aug. 2022.[PDF][Share]【ESI Highly Cited Paper，ESI高被引论文】

  7. Z. J. Wang(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Lin, W. J. Yu, H. Wang, S. Kwong, and J. Zhang, “Automatic niching differential evolution with contour prediction approach for multimodal optimization problems,” IEEE Transactions on Evolutionary Computation, vol. 24, no. 1, pp. 114-128, Feb. 2020.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  8. X. F. Liu(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), D. Deng, Y. Li, T. L. Gu, and J. Zhang, “An energy efficient ant colony system for virtual machine placement in cloud computing,” IEEE Transactions on Evolutionary Computation, vol. 22, no. 1, pp. 113-128, Feb. 2018.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  9. Z. J. Wang(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), S. Kwong, H. Jin, and J. Zhang, “Adaptive granularity learning distributed particle swarm optimization for large-scale optimization,” IEEE Transactions on Cybernetics, vol. 51, no. 3, pp. 1175-1188, March. 2021.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  10. Z. J. Wang(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), W. J. Yu, Y. Lin, J. Zhang, T.-L. Gu, and J. Zhang, “Dynamic group learning distributed particle swarm optimization for large-scale optimization and its application in cloud workflow scheduling,” IEEE Transactions on Cybernetics, vol. 50, no. 6, pp. 2715-2729, June 2020.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  11. Z. G. Chen(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Lin, Y. J. Gong,T. L. Gu, F. Zhao, H. Q. Yuan, X. Chen, Q. Li, and J. Zhang, “Multiobjective cloud workflow scheduling: A multiple populations ant colony system approach,” IEEE Transactions on Cybernetics, vol. 49, no. 8, pp. 2912-2926, Aug. 2019.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  12. S. Z. Zhou(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), Z. G. Chen, and J. Zhang, “A multi-objective ant colony system algorithm for airline crew rostering problem with fairness and satisfaction,” IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 11, pp. 6784-6798, Nov. 2021.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  13. Zhi-Hui Zhan(詹志辉), L. Shi, K. C. Tan, and J. Zhang, “A survey on evolutionary computation for complex continuous optimization,” Artificial Intelligence Review, vol. 55, no. 1, pp. 59-110, Jan. 2022.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  14. Zhi-Hui Zhan(詹志辉), J. Y. Li, and J. Zhang, “Evolutionary deep learning: A survey,” Neurocomputing, vol. 483, pp. 42-58, April 2022.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  15. Zhi-Hui Zhan(詹志辉), X. F. Liu, Y. J. Gong, J. Zhang, H. S. H. Chung, and Y. Li, “Cloud computing resource scheduling and a survey of its evolutionary approaches,” ACM Computing Surveys, vol. 47, no. 4, Article 63, pp. 1-33, Jul. 2015.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  16. Y. H. Li, Zhi-Hui Zhan(詹志辉)(Corresponding Author), S. J. Lin, J. Zhang, and X. N. Luo, “Competitive and cooperative particle swarm optimization with information sharing mechanism for global optimization problems,” Information Sciences, vol. 293, no. 1, pp. 370-382, Feb. 2015.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  17. Z. G. Chen(Student), Y. Lin, Y. J. Gong, Zhi-Hui Zhan(詹志辉), and J. Zhang, “Maximizing lifetime of range-adjustable wireless sensor networks: A neighborhood-based estimation of distribution algorithm,” IEEE Transactions on Cybernetics, vol. 51, no. 11, pp. 5433-5444, Nov. 2021.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  18. W. Chen, J. Zhang, Y. Lin, N. Chen, Zhi-Hui Zhan(詹志辉), H. Chung, Y. Li, and Y. Shi, “Particle swarm optimization with an aging leader and challengers,” IEEE Transactions on Evolutionary Computation, vol. 17, no. 2, pp. 241-258, April. 2013.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  19. Y. Gong, W. Chen, Zhi-Hui Zhan(詹志辉), J. Zhang, Y. Li, Q. Zhang, and J. Li, “Distributed evolutionary algorithms and their models: A survey of the state-of-the-art,” Applied Soft Computing, vol. 34, pp. 286-300, Sept. 2015.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  20. J. Shen, C. Wang, T. Li, X. Chen, X. Huang, and Zhi-Hui Zhan(詹志辉), “Secure data uploading scheme for a smart home system,” Information Sciences, vol. 453, pp. 186-197, Jul. 2018.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

Survey Papers

  1. Y. Jiang, X. X. Xu, M. Y. Zheng, and Zhi-Hui Zhan(詹志辉), “Evolutionary computation for unmanned aerial vehicle path planning: A survey,” Artificial Intelligence Review, vol. 57, Article No. 267, 2024.[PDF]

  2. Zhi-Hui Zhan(詹志辉), L. Shi, K. C. Tan, and J. Zhang, “A survey on evolutionary computation for complex continuous optimization,” Artificial Intelligence Review, vol. 55, no. 1, pp. 59-110, Jan. 2022.[PDF]

  3. J. Y. Li(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Evolutionary computation for expensive optimization: A survey,” Machine Intelligence Research, vol. 19, no. 1, pp. 3-23, Jan. 2022.[PDF]

  4. Zhi-Hui Zhan(詹志辉), J. Y. Li, and J. Zhang, “Evolutionary deep learning: A survey,” Neurocomputing, vol. 483, pp. 42-58, April 2022.[PDF]

  5. Z. G. Chen(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), S. Kwong, and J. Zhang, “Evolutionary computation for intelligent transportation in smart cities: A survey,” IEEE Computational Intelligence Magazine, vol. 17, no. 2, pp. 83-102, May, 2022.[PDF]

  6. J. R. Jian(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Large-scale evolutionary optimization: a survey and experimental comparative study,” International Journal of Machine Learning and Cybernetics, vol. 11, no. 3, pp. 729–745, March. 2020.[PDF]

  7. Zhi-Hui Zhan(詹志辉), X. F. Liu, Y. J. Gong, J. Zhang, H. S. H. Chung, and Y. Li, “Cloud computing resource scheduling and a survey of its evolutionary approaches,” ACM Computing Surveys, vol. 47, no. 4, Article 63, pp. 1-33, Jul. 2015.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  8. Y. Gong, W. Chen, Zhi-Hui Zhan(詹志辉), J. Zhang, Y. Li, Q. Zhang, and J. Li, “Distributed evolutionary algorithms and their models: A survey of the state-of-the-art,” Applied Soft Computing, vol. 34, pp. 286-300, Sept. 2015.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  9. J. Zhang, Zhi-Hui Zhan(詹志辉), Y. Lin, N. Chen, Y. J. Gong, J. H. Zhong, H. S. H. Chung, Y. Li, and Y. H. Shi, “Evolutionary computation meets machine learning: A survey,” IEEE Computational Intelligence Magazine, vol. 6, no. 4, pp. 68-75, Nov. 2011.[PDF]

Journal Papers [Early][2024][2023][2022][2021][2020][2019][2018][2017][2016][2015][2014][2013][2012][2011][2010][2009]

    [Early Access]

  1. Q. T. Yang, J. Y. Li, Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Jiang, Y. Jin,and J. Zhang, “A hierarchical and ensemble surrogate-assisted evolutionary algorithm with model reduction for expensive many-objective optimization,” IEEE Transactions on Evolutionary Computation, DOI:10.1109/TEVC.2024.3440354. Aug. 2024.[PDF]

  2. J. Hong(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), L. He, Z. Xu, and J. Zhang, “Protein structure prediction using a new optimization-based evolutionary and explainable artificial intelligence approach,” IEEE Transactions on Evolutionary Computation, DOI: 10.1109/TEVC.2024.3365814. Feb. 2024.[PDF]

  3. Y. Jiang(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. C. Tan, S. Kwong, and J. Zhang, “Knowledge structure preserving-based evolutionary many-task optimization,” IEEE Transactions on Evolutionary Computation, DOI: 10.1109/TEVC.2024.3355781. Jan. 2024.[PDF]

  4. Q. T. Yang, Zhi-Hui Zhan(詹志辉)(Corresponding Author), X. F. Liu, J. Y. Li, and J. Zhang, “Grid classification-based surrogate-assisted particle swarm optimization for expensive multiobjective optimization,” IEEE Transactions on Evolutionary Computation, DOI:10.1109/TEVC.2023.3340678. Dec. 2023.[PDF]

  5. X. F. Li, Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Transfer-based particle swarm optimization for large-scale dynamic optimization with changing variable interactions,” IEEE Transactions on Evolutionary Computation, DOI:10.1109/TEVC.2023.3326327. Oct. 2023.[PDF]

  6. J. Y. Li, Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Li, and J. Zhang, “Multiple tasks for multiple objectives: A new multiobjective optimization method via multitask optimization,” IEEE Transactions on Evolutionary Computation, DOI:10.1109/TEVC.2023.3294307. Jul. 2023.[PDF]

  7. Y. Jiang(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. C. Tan, and J. Zhang, “Knowledge learning for evolutionary computation,” IEEE Transactions on Evolutionary Computation, DOI:10.1109/TEVC.2023.3278132. May 2023.[PDF]

  8. S. Gao, Zhi-Hui Zhan(詹志辉), “Fractional order differential evolution,” IEEE Transactions on Evolutionary Computation, DOI:10.1109/TEVC.2024.3382047. Mar. 2024.[PDF]

  9. H. Ouyang, D. Liu, S. Li, W. Ding, and Zhi-Hui Zhan(詹志辉), “Two-stage deep feature selection method using voting differential evolution algorithm for pneumonia detection from chest X-Ray images,” IEEE Transactions on Emerging Topics in Computational Intelligence, DOI: 10.1109/TETCI.2024.3425285, Jul. 2024.[PDF]

  10. T. Li, Y. Qian, F. Li, X. Liang, and Zhi-Hui Zhan(詹志辉), “Feature subspace learning-based binary differential evolution algorithm for unsupervised feature selection,” IEEE Transactions on Big Data, DOI:10.1109/TBDATA.2024.3378090. Mar. 2024.[PDF]

    11. [2024]

  11. Y. Jiang(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. C. Tan, and J. Zhang, “Block-level knowledge transfer for evolutionary multitask optimization,” IEEE Transactions on Cybernetics, vol. 54, no. 1, pp. 558-571, Jan. 2024.[PDF]

  12. X. F. Liu, Y. Fang, Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. L. Jiang, and J. Zhang, “A cooperative evolutionary computation algorithm for dynamic multiobjective multi-AUV path planning,” IEEE Transactions on Industrial Informatics, vol. 20, no. 1, pp. 669-680, Jan. 2024.[PDF][Share]

  13. C. Wang, B. Sun, K. J. Du, J. Y. Li,Zhi-Hui Zhan(詹志辉)(Corresponding Author), S. W. Jeon, H. Wang, and J. Zhang, “A novel evolutionary algorithm with column and sub-block local search for Sudoku puzzles,” IEEE Transactions on Games, vol. 16, no. 1, pp. 162-172, Mar. 2024.[PDF][Share]

  14. Y. F. Ge, H. Wang, E. Bertino,Zhi-Hui Zhan(詹志辉)(Corresponding Author), J. Cao, Y. Zhang, and J. Zhang, “Evolutionary dynamic database partitioning optimization for privacy and utility,” IEEE Transactions on Dependable and Secure Computing,vol. 21, no. 4, pp. 2296-2311, Jul. 2024.[PDF]

  15. Y. Jiang, X. X. Xu, M. Y. Zheng, and Zhi-Hui Zhan(詹志辉), “Evolutionary computation for unmanned aerial vehicle path planning: A survey,” Artificial Intelligence Review, vol. 57, Article No. 267, 2024.[PDF]

    16. [2023]

  16. Zhi-Hui Zhan(詹志辉)(Corresponding Author), J. Y. Li, S. Kwong, and J. Zhang, “Learning-aid evolution for optimization,” IEEE Transactions on Evolutionary Computation, vol. 27, no. 6, pp. 1794–1808, Dec. 2023.[PDF]

  17. X. F. Liu, X. X. Xu, Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Fang, and J. Zhang, “Interaction-based prediction for dynamic multiobjective optimization,” IEEE Transactions on Evolutionary Computation, vol. 27, no. 6, pp. 1881-1895, Dec. 2023.[PDF]

  18. Y. Jiang(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. C. Tan, and J. Zhang, “A bi-objective knowledge transfer framework for evolutionary many-task optimization,” IEEE Transactions on Evolutionary Computation, vol. 27, no. 5, pp. 1514-1528, Oct. 2023.[PDF][Share]

  19. Q. T. Yang(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), S. Kwong, and J. Zhang, “Multiple populations for multiple objectives framework with bias sorting for many-objective optimization,” IEEE Transactions on Evolutionary Computation, vol. 27, no. 5, pp. 1340–1354, Oct. 2023.[PDF][Share]

  20. Z. J. Wang, J. R. Jian, Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Li, S. Kwong, and J. Zhang, “Gene targeting differential evolution: A simple and efficient method for large scale optimization,” IEEE Transactions on Evolutionary Computation, vol. 27, no. 4, pp. 964-979, Aug. 2023.[PDF][Share]【ESI Highly Cited Paper，ESI高被引论文】

  21. S. H. Wu(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. C. Tan, and J. Zhang, “Orthogonal transfer for multitask optimization,” IEEE Transactions on Evolutionary Computation, vol. 27, no. 1, pp. 185-200, Jan. 2023. (DOI: 10.1109/TEVC.2022.3160196. March. 2022.)[PDF-online][PDF][Share][Share2]【ESI Highly Cited Paper，ESI高被引论文】

  22. S. H. Wu(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. C. Tan, and J. Zhang, “Transferable adaptive differential evolution for many-task optimization,” IEEE Transactions on Cybernetics, vol. 53, no. 11, pp. 7295-7308, Nov. 2023.[PDF]

  23. J. Y. Li(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. C. Tan, and J. Zhang, “Dual differential grouping: A more general decomposition method for large-scale optimization,” IEEE Transactions on Cybernetics, vol. 53, no. 6, pp. 3624-3638, June 2023.[PDF][Share]

  24. J. Y. Li(Student), K. J. Du, Zhi-Hui Zhan(詹志辉)(Corresponding Author), H. Wang, and J. Zhang, “Distributed differential evolution with adaptive resource allocation,” IEEE Transactions on Cybernetics, vol. 53, no. 5, pp. 2791-2804, May 2023.[PDF][Share]

  25. Y. Jiang(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. C. Tan, and J. Zhang, “Optimizing niching centers for multimodal optimization,” IEEE Transactions on Cybernetics, vol. 53, no. 4, pp. 2544-2557, April 2023.[PDF][Share]

  26. S. C. Liu(Student), Z. G. Chen, Zhi-Hui Zhan(詹志辉)(Corresponding Author), S. W. Jeon, S. Kwong, and J. Zhang, “Many-objective job shop scheduling: A multiple populations for multiple objectives-based genetic algorithm approach,” IEEE Transactions on Cybernetics, vol. 53, no. 3, pp. 1460-1474, March 2023.[PDF][Share]

  27. J. Y. Li(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), J. Xu, S. Kwong, and J. Zhang, “Surrogate-assisted hybrid-model estimation of distribution algorithm for mixed-variable hyperparameter optimization in convolutional neural networks,” IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 5, pp. 2338-2352, May 2023.[PDF][Share]

  28. X. F. Liu, Y. Fang, Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Strength learning particle swarm optimization for multiobjective multirobot task scheduling,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 53, no. 7, pp. 4052-4063, Jul. 2023.[PDF][Share]

  29. X. Zhang, B. W. Ding, X. X. Xu, J. Y. Li, Zhi-Hui Zhan(詹志辉)(Corresponding Author), P. Qian, W. Fang, K. K. Lai, and J. Zhang, “Graph-based deep decomposition for overlapping large-scale optimization problems,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 53, no. 4, pp. 2374-2386, April. 2023.[PDF][Share]

  30. Z. J. Wang,Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Li, S. Kwong, S. W. Jeon, and J. Zhang, “Fitness and distance based local search with adaptive differential evolution for multimodal optimization problems,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 7, no. 3, pp. 684-699, June 2023.[PDF][Share]

  31. M. Gao(Student), J. Y. Li(Student), C. H. Chen, Y. Li, J. Zhang,Zhi-Hui Zhan(詹志辉)(Corresponding Author), “Enhanced multi-task learning and knowledge graph-based recommender system,” IEEE Transactions on Knowledge and Data Engineering,vol. 35, no. 10, pp. 10281-10294, Oct. 2023.[PDF][Share]

  32. J. Q. Yang(Student), Q. T. Yang(Student), K. J. Du, C. H. Chen, H. Wang, S. W. Jeon, J. Zhang,Zhi-Hui Zhan(詹志辉)(Corresponding Author), “Bi-directional feature fixation-based particle swarm optimization for large-scale feature selection,” IEEE Transactions on Big Data,vol. 9, no. 3, pp. 1004-1017, June 2023.[PDF][Share]

  33. K. Guo, Z. Chen, X. Lin, L. Wu, Zhi-Hui Zhan(詹志辉), Y. Chen, and W. Guo, “Community detection based on multiobjective particle swarm optimization and graph attention variational autoencoder,” IEEE Transactions on Big Data, vol. 9, no. 2, pp. 569-583, April 2023.[PDF]

  34. Y. Q. Wang(Student), J. Y. Li(Student), C. H. Chen, J. Zhang, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), “Scale adaptive fitness evaluation-based particle swarm optimization for hyperparameter and architecture optimization in neural networks and deep learning,” CAAI Transactions on Intelligence Technology, vol. 8, no. 3, pp. 849-862, Sept. 2023.[PDF]

  35. X. F. Liu, Zhi-Hui Zhan(詹志辉)(Corresponding Author), J. Zhang, “Incremental particle swarm optimization for large-scale dynamic optimization with changing variable interactions,” Applied Soft Computing, vol. 141, pp. 110320, Jul. 2023.[PDF]

    36. [2022]

  36. Zhi-Hui Zhan(詹志辉), L. Shi, K. C. Tan, and J. Zhang, “A survey on evolutionary computation for complex continuous optimization,” Artificial Intelligence Review, vol. 55, no. 1, pp. 59-110, Jan. 2022.[PDF]

  37. J. Y. Li(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Evolutionary computation for expensive optimization: A survey,” Machine Intelligence Research, vol. 19, no. 1, pp. 3-23, Jan. 2022.[PDF]

  38. Zhi-Hui Zhan(詹志辉), J. Y. Li, and J. Zhang, “Evolutionary deep learning: A survey,” Neurocomputing, vol. 483, pp. 42-58, April 2022.[PDF]

  39. Z. G. Chen(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), S. Kwong, and J. Zhang, “Evolutionary computation for intelligent transportation in smart cities: A survey,” IEEE Computational Intelligence Magazine, vol. 17, no. 2, pp. 83-102, May, 2022.[PDF]

  40. J. Y. Li(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. C. Tan, and J. Zhang, “A meta-knowledge transfer-based differential evolution for multitask optimization,” IEEE Transactions on Evolutionary Computation, vol. 26, no. 4, pp. 719-734, Aug. 2022.[PDF][Share]【ESI Highly Cited Paper，ESI高被引论文】

  41. X. Zhang, Zhi-Hui Zhan(詹志辉)(Corresponding Author), W. Fang, P. Qian, and J. Zhang, “Multipopulation ant colony system with knowledge-based local searches for multiobjective supply chain configuration,” IEEE Transactions on Evolutionary Computation, vol. 26, no. 3, pp. 512-526, Jun. 2022.[PDF][Share]

  42. S. C. Liu(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. C. Tan, and J. Zhang, “A multi-objective framework for many-objective optimization,” IEEE Transactions on Cybernetics, vol. 52, no. 12, pp. 13654-13668, Dec. 2022.[PDF][Share]

  43. X. F. Liu, Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Resource-aware distributed differential evolution for training expensive neural-network-based controller in power electronic circuit,” IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 11, pp. 6286-6296, Nov. 2022.[PDF][Share]

  44. Zhi-Hui Zhan(詹志辉), J. Zhang, Y. Lin, J. Y. Li, T. Huang, X. Q. Guo, F. F. Wei, S. Kwong, X. Y. Zhang, and R. You, “Matrix-based evolutionary computation,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 6, no. 2, pp. 315-328, April 2022.[PDF]

  45. L. J. Wu(Student), L. Shi(Student),Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. K. Lai, and J. Zhang, “A buffer-based ant colony system approach for dynamic cold chain logistics scheduling,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 6, no. 6, pp. 1438-1452, Dec. 2022.[PDF][Share]

  46. J. Y. Li(Student), X. Y. Deng, Zhi-Hui Zhan(詹志辉)(Corresponding Author), L. Yu, K. C. Tan, K. K. Lai, and J. Zhang, “A multipopulation multiobjective ant colony system considering travel and prevention costs for vehicle routing in COVID-19-like epidemics,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 12, pp. 25062-25076, Dec. 2022.[PDF][PDF-online][Share]

  47. L. J. Wu(Student), Z. G. Chen, C. H. Chen, Y. Li, S. W. Jeon, J. Zhang, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), “Real environment-aware multisource data-associated cold chain logistics scheduling: A multiple population-based multiobjective ant colony system approach ,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 12, pp. 23613-23627, Dec. 2022.[PDF][PDF-online][Share]

  48. R. Wang(Student), F. Ji, Y. Jiang, S. H. Wu, S. Kwong, J. Zhang, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), “An adaptive ant colony system based on variable range receding horizon control for berth allocation problem,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 11, pp. 21675-21686, Nov. 2022.[PDF][Share]

  49. L. Shi(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), D. Liang, and J. Zhang, “Memory-based ant colony system approach for multi-source data associated dynamic electric vehicle dispatch optimization,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 10, pp. 17491-17505, Oct. 2022.[PDF][Share]

  50. Y. F. Ge(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), J. Cao, H. Wang, Y. Zhang, K.-K. Lai, and J. Zhang, “DSGA: A distributed segment-based genetic algorithm for multi-objective outsourced database partitioning,” Information Sciences, DOI: 10.1016/j.ins.2022.09.003, 2022.[PDF]

  51. T. Li, Zhi-Hui Zhan(詹志辉)(Corresponding Author), J.-C. Xu, Q. Yang, and Y.-Y. Ma,“A binary individual search strategy-based bi-objective evolutionary algorithm for high-dimensional feature selection,” Information Sciences, vol. 610, pp. 651-673, 2022.[PDF]

  52. X. X. Shao, Y. J. Gong, Zhi-Hui Zhan(詹志辉), and J. Zhang, “Bipartite cooperative coevolution for energy-aware coverage path planning of UAVs,” IEEE Transactions on Artificial Intelligence, vol. 3, no. 1, pp. 29-42, Feb. 2022.[PDF]

  53. A. Song, W. N. Chen, X. N. Luo, Zhi-Hui Zhan(詹志辉), and J. Zhang, “Scheduling workflows with composite tasks: A nested particle swarm optimization approach,” IEEE Transactions on Services Computing, vol. 15, no. 2, pp. 1074-1088, March. 2022.[PDF]

    54. [2021]

  54. J. R. Jian(Student), Z. G. Chen, Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Region encoding helps evolutionary computation evolve faster: A new solution encoding scheme in particle swarm for large-scale optimization,” IEEE Transactions on Evolutionary Computation, vol. 25, no. 4, pp. 779-793, Aug. 2021.[PDF]

  55. S. H. Wu(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “SAFE: Scale-adaptive fitness evaluation method for expensive optimization problems,” IEEE Transactions on Evolutionary Computation, vol. 25, no. 3, pp. 478-491, Jun. 2021.[PDF]

  56. J. Y. Li(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), R. D. Liu, C. Wang, S. Kwong, and J. Zhang, “Generation-level parallelism for evolutionary computation: A pipeline-based parallel particle swarm optimization,” IEEE Transactions on Cybernetics, vol. 51, no. 10, pp. 4848-4859, Oct. 2021.[PDF]

  57. Y. F. Ge(Student), W. J. Yu, J. Cao, H. Wang, Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Zhang, and J. Zhang, “Distributed memetic algorithm for outsourced database fragmentation,” IEEE Transactions on Cybernetics,vol. 51, no. 10, pp. 4808-4821, Oct. 2021.[PDF]

  58. J. Y. Li(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), H. Wang, and J. Zhang, “Data-driven evolutionary algorithm with perturbation-based ensemble surrogates,” IEEE Transactions on Cybernetics, vol. 51, no. 8, pp. 3925-3937, Aug. 2021.[PDF]

  59. Z. J. Wang(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), S. Kwong, H. Jin, and J. Zhang, “Adaptive granularity learning distributed particle swarm optimization for large-scale optimization,” IEEE Transactions on Cybernetics, vol. 51, no. 3, pp. 1175-1188, March. 2021.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  60. S. Z. Zhou(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), Z. G. Chen, and J. Zhang, “A multi-objective ant colony system algorithm for airline crew rostering problem with fairness and satisfaction,” IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 11, pp. 6784-6798, Nov. 2021.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  61. H. Zhao(Student), Z. G. Chen, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), S. Kwang, and J. Zhang, “Multiple populations co-evolutionary particle swarm optimization for multi-objective cardinality constrained portfolio optimization problem,” Neurocomputing, vol. 430, pp. 58-70, Mar. 2021.[PDF]

  62. Z. G. Chen(Student), Y. Lin, Y. J. Gong, Zhi-Hui Zhan(詹志辉), and J. Zhang, “Maximizing lifetime of range-adjustable wireless sensor networks: A neighborhood-based estimation of distribution algorithm,” IEEE Transactions on Cybernetics, vol. 51, no. 11, pp. 5433-5444, Nov. 2021.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

    63. [2020]

  63. J. Y. Li(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), C. Wang, H. Jin, and J. Zhang, “Boosting data-driven evolutionary algorithm with localized data generation,” IEEE Transactions on Evolutionary Computation, vol. 24, no. 5, pp. 923-937, Oct. 2020.[PDF]

  64. Z. G. Chen(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), H. Wang, and J. Zhang, “Distributed individuals for multiple peaks: A novel differential evolution for multimodal optimization problems,” IEEE Transactions on Evolutionary Computation, vol. 24, no. 4, pp. 708-719, Aug. 2020.[PDF]

  65. Z. J. Wang(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Lin, W. J. Yu, H. Wang, S. Kwong, and J. Zhang, “Automatic niching differential evolution with contour prediction approach for multimodal optimization problems,” IEEE Transactions on Evolutionary Computation, vol. 24, no. 1, pp. 114-128, Feb. 2020.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  66. X. Xia, L. Gui, F. Yu, H. Wu, B. Wei, Y. Zhang, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), “Triple archives particle swarm optimization,” IEEE Transactions on Cybernetics, vol. 50, no. 12, pp. 4862-4875, Dec. 2020.[PDF]

  67. Zhi-Hui Zhan(詹志辉), Z. J. Wang, H. Jin, and J. Zhang, “Adaptive distributed differential evolution,” IEEE Transactions on Cybernetics, vol. 50, no. 11, pp. 4633-4647, Nov. 2020.[PDF]

  68. X. Zhang(Student), K. J. Du, Zhi-Hui Zhan(詹志辉)(Corresponding Author), S. Kwong, T. L. Gu, and J. Zhang, “Cooperative co-evolutionary bare-bones particle swarm optimization with function independent decomposition for large-scale supply chain network design with uncertainties,” IEEE Transactions on Cybernetics, vol. 50, no. 10, pp. 4454-4468, Oct. 2020.[PDF]

  69. H. Zhao(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Lin, X. Chen, X. N. Luo, J. Zhang, S. Kwong, and J. Zhang, “Local binary pattern-based adaptive differential evolution for multimodal optimization problems,” IEEE Transactions on Cybernetics, vol. 50, no. 7, pp. 3343-3357, July. 2020.[PDF]

  70. Z. J. Wang(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), W. J. Yu, Y. Lin, J. Zhang, T.-L. Gu, and J. Zhang, “Dynamic group learning distributed particle swarm optimization for large-scale optimization and its application in cloud workflow scheduling,” IEEE Transactions on Cybernetics, vol. 50, no. 6, pp. 2715-2729, June 2020.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  71. X. F. Liu(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), T. L. Gu, S. Kwong, Z. Lu, H. B.-L. Duh, and J. Zhang, “Neural network-based information transfer for dynamic optimization,” IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 5, pp. 1557-1570, May 2020.[PDF]

  72. D. Liang(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Zhang, and J. Zhang, “An efficient ant colony system approach for new energy vehicle dispatch problem,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 11, pp. 4784-4797, Nov. 2020.[PDF]

  73. X. Xia, L. Gui, G. He, B. Wei, Y. Zhang, F. Yu, H. Wu, Zhi-Hui Zhan(詹志辉)(Corresponding Author), “An expanded particle swarm optimization based on multi-exemplar and forgetting ability,” Information Sciences, vol. 508, pp. 105-120, Jan. 2020.[PDF]

  74. J. R. Jian(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Large-scale evolutionary optimization: a survey and experimental comparative study,” International Journal of Machine Learning and Cybernetics, vol. 11, no. 3, pp. 729–745, March. 2020.[PDF]

  75. T. Huang, Y. J. Gong, Y. H. Zhang, Zhi-Hui Zhan(詹志辉), and J. Zhang, “Automatic planning of multiple itineraries: A niching genetic evolution approach,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 10, pp. 4225-4240, Oct. 2020.[PDF]

  76. Y. J. Wang, Z. Cai, Zhi-Hui Zhan(詹志辉), B. Zhao, X. Tong, and L. Qi, “Walrasian equilibrium-based multiobjective optimization for task allocation in mobile crowdsourcing,” IEEE Transactions on Computational Social Systems, vol. 7, no. 4, pp. 1033-1046, Aug. 2020.[PDF]

    77. [2019]

  77. X. F. Liu(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Gao, J. Zhang, S. Kwong, and J. Zhang, “Coevolutionary particle swarm optimization with bottleneck objective learning strategy for many-objective optimization,” IEEE Transactions on Evolutionary Computation, vol. 23, no. 4, pp. 587-602, Aug. 2019.[PDF]

  78. Z. G. Chen(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Lin, Y. J. Gong,T. L. Gu, F. Zhao, H. Q. Yuan, X. Chen, Q. Li, and J. Zhang, “Multiobjective cloud workflow scheduling: A multiple populations ant colony system approach,” IEEE Transactions on Cybernetics, vol. 49, no. 8, pp. 2912-2926, Aug. 2019.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  79. X. F. Liu(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Lin, W. N. Chen, Y. J. Gong, T. L. Gu, H. Q. Yuan, and J. Zhang, “Historical and heuristic-based adaptive differential evolution,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 49, no. 12, pp. 2623-2635, Dec. 2019.[PDF]

  80. Y. Wang, Z. Cai, Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Gong, and X. Tong, “An optimization and auction-based incentive mechanism to maximize social welfare for mobile crowdsourcing,” IEEE Transactions on Computational Social Systems, vol. 6, no. 3, pp. 414-429, Jun. 2019.[PDF]

  81. Y. Lin, Y. S. Jiang, Y. J. Gong, Zhi-Hui Zhan(詹志辉), and J. Zhang, “A discrete multiobjective particle swarm optimizer for automated assembly of parallel cognitive diagnosis tests,” IEEE Transactions on Cybernetics, vol. 49, no. 7, pp. 2792-2805, Jul. 2019.[PDF]

  82. G. Xu, Q. Cui, X. Shi, H. Ge, Zhi-Hui Zhan(詹志辉), H. P. Lee, Y. Liang, R. Tai, and C. Wu, “Particle swarm optimization based on dimensional learning strategy,” Swarm and Evolutionary Computation, vol. 45, pp. 33-51, March. 2019.[PDF]

    83. [2018]

  83. Z. J. Wang(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Lin, W. J. Yu, H. Q. Yuan, T. L. Gu, S. Kwong, and J. Zhang, “Dual-strategy differential evolution with affinity propagation clustering for multimodal optimization problems,” IEEE Transactions on Evolutionary Computation, vol. 22, no. 6, pp. 894-908, Dec. 2018.[PDF]

  84. X. F. Liu(Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), D. Deng, Y. Li, T. L. Gu, and J. Zhang, “An energy efficient ant colony system for virtual machine placement in cloud computing,” IEEE Transactions on Evolutionary Computation, vol. 22, no. 1, pp. 113-128, Feb. 2018.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  85. Y. F. Ge(Student), W. J. Yu, Y. Lin, Y. J. Gong, Zhi-Hui Zhan(詹志辉), W. N. Chen, and J. Zhang, “Distributed differential evolution based on adaptive mergence and split for large-scale optimization,” IEEE Transactions on Cybernetics, vol. 48, no. 7, pp. 2166-2180, Jul. 2018.[PDF]

    86. [2017]

  86. Zhi-Hui Zhan(詹志辉), X. Liu, H. Zhang, Z. Yu, J. Weng, Y. Li, T. Gu, and J. Zhang, “Cloudde: A heterogeneous differential evolution algorithm and its distributed cloud version,” IEEE Transactions on Parallel and Distributed Systems, vol. 28, no. 3, pp. 704-716, March. 2017.[PDF]

    87. [2016]

  87. X. Zhang , J. Zhang, Y. Gong, Zhi-Hui Zhan(詹志辉), W. Chen, and Y. Li, “Kuhn-munkres parallel genetic algorithm for the set cover problem and its application to large-scale wireless sensor networks,” IEEE Transactions on Evolutionary Computation, vol. 20, no. 5, pp. 695-710, Oct. 2016.[PDF]

  88. Q. Lin, J. Chen, Zhi-Hui Zhan(詹志辉), W. Chen, C. Coello Coello, Y. Yin, C. Lim, and J. Zhang, “A hybrid evolutionary immune algorithm for multiobjective optimization problems,” IEEE Transactions on Evolutionary Computation, vol. 20, no. 5, pp. 711-729, Oct. 2016.[PDF]

  89. Y. L. Li, Y. Zhou, Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “A primary theoretical study on decomposition-based multiobjective evolutionary algorithms,” IEEE Transactions on Evolutionary Computation, vol. 20, no. 4, pp. 563-576, Aug. 2016.[PDF]

  90. Y. L. Li, Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. J. Gong, J. Zhang, Y. Li, and Q. Li, “Fast micro-differential evolution for topological active net optimization,” IEEE Transactions on Cybernetics, vol. 46, no. 6, pp. 1411-1423, Jun. 2016.[PDF]

  91. Q. Liu, W. Wei, H. Yuan, Zhi-Hui Zhan(詹志辉)(Corresponding Author), and Y. Li, “Topology selection for particle swarm optimization,” Information Sciences, vol. 363, no. 1, pp. 154-173, Oct. 2016.[PDF]

    92. [2015]

  92. Zhi-Hui Zhan(詹志辉), X. F. Liu, Y. J. Gong, J. Zhang, H. S. H. Chung, and Y. Li, “Cloud computing resource scheduling and a survey of its evolutionary approaches,” ACM Computing Surveys, vol. 47, no. 4, Article 63, pp. 1-33, Jul. 2015.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  93. Y. L. Li, Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. J. Gong, W. N. Chen, J. Zhang, and Y. Li, “Differential evolution with an evolution path: A DEEP evolutionary algorithm,” IEEE Transactions on Cybernetics, vol. 45, no. 9, pp. 1798-1810, Sept. 2015.[PDF]

  94. N. Chen, W. Chen. Y. Gong, Zhi-Hui Zhan(詹志辉), J. Zhang, Y. Li, and Y. S. Tan, “An evolutionary algorithm with double-level archives for multiobjective optimization,” IEEE Transactions on Cybernetics, vol. 45, no. 9, pp. 1851-1863, Sept. 2015.[PDF]

  95. Y. H. Li, Zhi-Hui Zhan(詹志辉)(Corresponding Author), S. J. Lin, J. Zhang, and X. N. Luo, “Competitive and cooperative particle swarm optimization with information sharing mechanism for global optimization problems,” Information Sciences, vol. 293, no. 1, pp. 370-382, Feb. 2015.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  96. Y. Gong, W. Chen, Zhi-Hui Zhan(詹志辉), J. Zhang, Y. Li, Q. Zhang, and J. Li, “Distributed evolutionary algorithms and their models: A survey of the state-of-the-art,” Applied Soft Computing, vol. 34, pp. 286-300, Sept. 2015.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

    97. [2014]

  97. W. Yu, M. Shen, W. Chen, Zhi-Hui Zhan(詹志辉), Y. Gong, Y. Lin, O. Liu, and J. Zhang, “Differential evolution with two-level parameter adaptation,” IEEE Transactions on Cybernetics, vol. 44, no. 7, pp. 1080-1099, Jul. 2014.[PDF]

    98. [2013]

  98. Zhi-Hui Zhan(詹志辉), J. Li, J. Cao, J. Zhang, H. Chung, and Y. H. Shi, “Multiple populations for multiple objectives: A coevolutionary technique for solving multiobjective optimization problems,” IEEE Transactions on Cybernetics, vol. 43, no. 2, pp. 445-463, April. 2013.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  99. W. Chen, J. Zhang, Y. Lin, N. Chen, Zhi-Hui Zhan(詹志辉), H. Chung, Y. Li, and Y. Shi, “Particle swarm optimization with an aging leader and challengers,” IEEE Transactions on Evolutionary Computation, vol. 17, no. 2, pp. 241-258, April. 2013.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

    100. [2012]

  100. Y. Gong, J. Zhang, H. Chung, W. Chen, Zhi-Hui Zhan(詹志辉), Y. Li, and Y. Shi, “An efficient resource allocation scheme using particle swarm optimization,” IEEE Transactions on Evolutionary Computation, vol. 16, no. 6, pp. 801-816, Dec. 2012.[PDF]

  101. Y. Gong, M. Shen, J. Zhang, O. Kaynak, W. Chen, and Zhi-Hui Zhan(詹志辉), “Optimizing RFID network planning by using a particle swarm optimization algorithm with redundant reader elimination,” IEEE Transactions on Industrial Informatics, vol. 8, no. 4, pp. 900-912, Nov. 2012.[PDF]

    102. [2011]

  102. Zhi-Hui Zhan(詹志辉), J. Zhang, Y. Li, and Y. H. Shi, “Orthogonal learning particle swarm optimization,” IEEE Transactions on Evolutionary Computation, vol. 15, no. 6, pp. 832-847, Dec. 2011.[PDF]【ESI Highly Cited Paper，ESI高被引论文】

  103. J. Zhang(导师), Zhi-Hui Zhan(詹志辉), Y. Lin, N. Chen, Y. J. Gong, J. H. Zhong, H. S. H. Chung, Y. Li, and Y. H. Shi, “Evolutionary computation meets machine learning: A survey,” IEEE Computational Intelligence Magazine, vol. 6, no. 4, pp. 68-75, Nov. 2011.[PDF]

    104. [2010]

  104. Zhi-Hui Zhan(詹志辉), J. Zhang, Y. Li, O. Liu, S. K. Kwok, W. H. Ip, and O. Kaynak, “An efficient ant colony system based on receding horizon control for the aircraft arrival sequencing and scheduling problem,” IEEE Transactions on Intelligent Transportation Systems, vol. 11, no. 2, pp. 399-412, Jun. 2010.[PDF]

    105. [2009]

  105. Zhi-Hui Zhan(詹志辉), J. Zhang, Y. Li, and H. Chung, “Adaptive particle swarm optimization,” IEEE Transactions on Systems, Man, and Cybernetics--Part B, vol. 39, no. 6, pp. 1362-1381, Dec. 2009.[PDF]【ESI Highly Cited Paper，ESI高被引论文，IEEE Trans. on SMC Part B和IEEE Trans. Cybernetics近25年来（1998年至今）刊印的共6600多篇论文中被引次数排名第2的论文】

Conference Papers [2023][2022][2021][2020][2019][2018][[2017][2016][2015][2014][2013][2012][2011][2010][2009][2008][2007]

    [2023]

  1. P. Y. Zhu (Student), S. H. Wu, K. J. Du, H. Wang, J. Zhang, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), “Diversity-driven multi-population particle swarm optimization for dynamic optimization problem,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2023),Lisboa, Portugal, Jul. 2023, pp. 107-110.[PDF]

  2. C. Zhang (Student), J. Y. Li, C. H. Chen, Y. Li, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), “Region-based evaluation particle swarm optimization with dual solution libraries for real-time traffic signal timing optimization,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2023),Lisboa, Portugal, Jul. 2023, pp. 111-118.[PDF]

  3. J. Q. Yang (Student), K. J. Du, C. H. Chen, H. Wang, and J. Zhang, and Zhi-Hui Zhan(詹志辉)(Corresponding Author),“Evolutionary multitasking bi-directional particle swarm optimization for high-dimensional feature selection,” in Proc. IEEE Congr. Evol. Comput. (CEC 2023), Chicago, USA, Jul. 2023, Accepted.[PDF]

  4. S. H. Wu (Student), J. Y. Li, Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Multi-view transfer with marginal and conditional alignment for many-task optimization,” in Proc. IEEE Congr. Evol. Comput. (CEC 2023), Chicago, USA, Jul. 2023, Accepted.[PDF]

  5. S. J. Jie, Y. Jiang, X. X. Xu, S. Kwong, J. Zhang, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), “Optimal peaks detected-based differential evolution for multimodal optimization problems,” in Proc. IEEE Int. Conf. Syst., Man, and Cybern. (SMC 2023), Hawaii, USA, May. 2023, Accepted.[PDF]

  6. M. Gao (Student), K. J. Du, J. Y. Li, H. Wang, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), “A robust two-part modeling strategy for knowledge graph enhanced recommender systems,” in Proc. Int. Conf. Adv. Comput. Intell. (ICACI2023), Seoul, Korea, May. 2023, pp. 1-7.[PDF]

  7. X. X. Xu (Student), Y. Jiang, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), “Evolutionary computation for berth allocation problems: A survey,” in Proc. Int. Conf. Neural Inf. Proces. (ICONIP2023), Changsha, China, Nov, 2023, Accepted.[PDF]

    8. [2022]

  8. Q. T. Yang (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Li, and J. Zhang, “Social learning particle swarm optimization with two-surrogate collaboration for offline data-driven multiobjective optimization,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2022),Boston, Jul. 2022, pp. 49-57.[PDF]

  9. H. R. Wang (Student), C. H. Chen, J. Zhang, and Zhi-Hui Zhan(詹志辉)(Corresponding Author),“Progressive sampling surrogate-assisted particle swarm optimization for large-scale expensive optimization,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2022),Boston, Jul. 2022, pp. 40-48.[PDF]

  10. Y. Q. Wang (Student), C. H. Chen, J. Zhang, and Zhi-Hui Zhan(詹志辉)(Corresponding Author),“Dropout topology-assisted bidirectional learning particle swarm optimization for neural architecture search,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2022),Boston, Jul. 2022, pp. 93-96.[PDF]

  11. Y. Jiang(Student), C. H. Chen, Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Li, and J. Zhang, “Adversarial differential evolution for multimodal optimization problems,” in Proc. IEEE Congr. Evol. Comput. (CEC 2022), Padua, Italy, Jul. 2022, pp. 1-8.[PDF]

  12. M. Gao (Student), C. H. Chen, Z. H. Gao, W. L. Chen, Y. Ren, S. Kwong, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), “A novel hierarchical discourse model for scientific article and it’s efficient top-k resampling-based text classification approach,” in Proc. IEEE Int. Conf. Syst., Man, and Cybern. (SMC 2022), Prague, Czech Republic, Oct. 2022, pp. 774-781.[PDF]

  13. J. R. Jian (Student), C. H. Chen, D. Liu, J. Zhang, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), “Can big population always bring better optimization ability to evolutionary computation for large-scale optimization?,” in Proc. IEEE Int. Conf. Syst., Man, and Cybern. (SMC 2022), Prague, Czech Republic, Oct. 2022, pp. 1468-1475.[PDF]

  14. Y. Jiang (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “A new and more challenging compositive multi-task optimization problem test suite,” in Proc. Int. Conf. Info. Sci. and Techno. (ICIST 2022), Kaifeng, China, Oct. 2022, pp. 132-138.[PDF]

    15. [2021]

  15. J. Y. Li (Student), K. J. Du, Zhi-Hui Zhan(詹志辉)(Corresponding Author), H. Wang, and J. Zhang, “Multi-criteria differential evolution: treating multitask optimization as multi-criteria optimization,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2021),Online, Jul. 2021, pp. 183-184.[PDF]

  16. S. H. Wu (Student), K. J. Du, Zhi-Hui Zhan(詹志辉)(Corresponding Author), H. Wang, and J. Zhang, “Historical information-based differential evolution for dynamic optimization problems,” in Proc. IEEE Congr. Evol. Comput. (CEC 2021), Kraków, Poland, Jun. 2021, pp. 119-126.[PDF]

  17. Z. J. Deng (Student), L. Y. Luo, Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Knowledge embedding-assisted multi-exemplar learning particle swarm optimization for traffic signal timing optimization,” in Proc. IEEE Congr. Evol. Comput. (CEC 2021), Kraków, Poland, Jun. 2021, pp. 248-255.[PDF]

  18. L. J. Wu (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), S. Kwong, and J. Zhang, “Real traffic distance-aware logistics scheduling,” in Proc. IEEE Int. Conf. Syst., Man, and Cybern. (SMC 2021), Melbourne, Australia, Oct. 2021, pp. 2912-2917.[PDF]

  19. Z. J. Deng (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), S. Kwong, and J. Zhang, “Multi-exemplar learning particle swarm optimization for regional traffic signal timing optimization with multi-intersections,” in Proc. IEEE Int. Conf. Syst., Man, and Cybern. (SMC 2021), Melbourne, Australia, Oct. 2021, pp. 2918-2923.[PDF]

  20. S. C. Liu (Student), C. Chen, Zhi-Hui Zhan(詹志辉)(Corresponding Author),and J. Zhang, “Multi-objective emergency resource dispatch based on coevolutionary multiswarm particle swarm optimization,” in Proc. Int. Conf. Series on Evol. Multi-Criterion Optimization (EMO 2021),Shenzhen, China, March. 2021, pp. 746-758.[PDF]

  21. Zhi-Hui Zhan(詹志辉)(Corresponding Author), S. H. Wu, and J. Zhang, “A new evolutionary computation framework for privacy-preserving optimization,” in Proc. Int. Conf. Advanced Comput. Intell. (ICACI 2021), Wanzhou, China, May. 2021, pp. 220-226.[PDF]

  22. L. Y. Luo (Student), L. Shi, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), “Investigation and improvement of distributed differential evolution algorithm Cloudde,” in Proc. Int. Conf. Advanced Comput. Intell. (ICACI 2021), Wanzhou, China, May. 2021, pp. 335-340.[PDF]

  23. J. Q. Yang (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), and T. Li, “Compressed-coding particle swarm optimization for large-scale feature selection,” in Proc. The 16th CCF Conference on Computer Supported Cooperative Work and Social Computing (ChineseCSCW 2021), Xiangtan, China, Nov. 2021, pp. 259-270.[PDF]

  24. H. R. Wang (Student), Y. Jiang, Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhong, “Multi-loop adaptive differential evolution for large-scale expensive optimization,” in Proc. The 16th CCF Conference on Computer Supported Cooperative Work and Social Computing (ChineseCSCW 2021), Xiangtan, China, Nov. 2021, pp. 301-315.[PDF]

  25. Y. X. Li (Student), J. Y. Li, Z. J. Wang, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), “Spatial-temporal graph neural network framework with multi-source local and global information fusion for traffic flow forecasting,” in Proc. The 16th CCF Conference on Computer Supported Cooperative Work and Social Computing (ChineseCSCW 2021), Xiangtan, China, Nov. 2021, pp. 371-385.[PDF]

  26. Z. Ma, B. Ding, X. Zhang, P. Qian, and Zhi-Hui Zhan(詹志辉), “Marine predators algorithm with stage-based repairment for the green supply network design,” in Proc. The 16th CCF Conference on Computer Supported Cooperative Work and Social Computing (ChineseCSCW 2021), Xiangtan, China, Nov. 2021, pp. 243-258.[PDF]

  27. X. F. Liu, B. C. Lin, Zhi-Hui Zhan(詹志辉), S. W. Jeon, and J. Zhang, “An efficient ant colony system for multi-robot task allocation with large-scale cooperative tasks and precedence constraints,” in Proc. IEEE Symposium Series on Computational Intelligence (SSCI 2021), Orlando, America, Dec. 2021, pp. 1-8.[PDF]

  28. W. Shen, C. Zhang, W. Fang, X. Zhang, Zhi-Hui Zhan(詹志辉), and J. C. W. Lin, “Efficient high-utility itemset mining based on a novel data structure,” in Proc. IEEE International Smart Cities Conference (ISC2 2021), Manchester, UK, Sept. 2021, pp. 1-6.[PDF]

    29. [2020]

  29. X. Zhang (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author),and J. Zhang, “Multiobjective direction driven local search for constrained supply chain configuration problem,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2020),Cancún, Mexico, Jul. 2020, pp. 299-300.[PDF]

  30. X. Zhang (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Adaptive population differential evolution with dual control strategy for large-scale global optimization problems,” in Proc. IEEE Congr. Evol. Comput. (CEC 2020), Glasgow, UK, Jul. 2020, pp. 1-7.[PDF]

  31. H. Zhao (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Adaptive guidance-based differential evolution with iterative feedback archive strategy for multimodal optimization problems,” in Proc. IEEE Congr. Evol. Comput. (CEC 2020), Glasgow, UK, Jul. 2020, pp. 1-8.[PDF]

  32. Z. G. Chen (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), D. Liu, S. Kwong, and J. Zhang, “Particle swarm optimization with hybrid ring topology for multimodal optimization problems,” in Proc. IEEE Int. Conf. Syst., Man, and Cybern. (SMC 2020), Toronto, Canada, Oct. 2020, pp. 2044-2049.[PDF]

  33. J. C. Chen (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), D. Liu, and J. Zhang, “A new and efficient genetic algorithm with promotion selection operator,” in Proc. IEEE Int. Conf. Syst., Man, and Cybern. (SMC 2020), Toronto, Canada, Oct. 2020, pp. 1532-1537.[PDF]

  34. Z. G. Chen (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Bridge connecting multiobjetive and multimodal: A new approach for multiobjetive optimization via multimodal optimization,” in Proc. IEEE Int. Conf. Information, Cybern., and Comput. Social Syst. (ICCSS 2020), Guangzhou, China, Nov. 2020, pp. 463-468.[PDF]

    35. [2019]

  35. L. J. Wu (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), X. M. Hu, P. Guo, Y. Zhang, and J. Zhang, “Multi-runway aircraft arrival scheduling:A receding horizon control based ant colony system approach,” in Proc. IEEE Congr. Evol. Comput. (CEC 2019), Wellington, New Zealand, Jun. 2019, pp. 538-545.[PDF]

  36. Y. F. Ge (Student), J. Cao, H. Wang, J. Yin, W. Yu, Zhi-Hui Zhan(詹志辉),and J. Zhang, “A benefit-driven genetic algorithm for balancing privacy and utility in database fragmentation,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2019), Prague, Czech Republic, Jul. 2019, pp. 771-776.[PDF]

  37. H. Zhao (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), W. N. Chen, X. N. Luo, T. L. Gu, R. C. Guan, L. Huang, and J. Zhang, “An improved selection operator for multi-objective optimization,” in Proc. Int. Symp. Neural Networks (ISNN 2019), Moscow, Russia, Jul. 2019, pp. 379-388.[PDF]

  38. X. Chen (Student), L. J. Wu, A. Mao, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), “A new learning scheme of emotion recognition from speech by using mean fourier parameters,” in Proc. Int. Conf. Advanced Comput. Intell. (ICACI 2019), Guilin, China, Jun. 2019, pp. 96-101.[PDF]

  39. Y. X. Li (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), H. Jin, and J. Zhang, “Cloudde-based distributed differential evolution for solving dynamic optimization problems,” in Proc. Int. Conf. Intell. Control and Information Processing (ICICIP 2019), Marrakesh, Morocco, Dec. 2019, pp. 94-99.[PDF]

    40. [2018]

  40. T. Ling, Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. X. Wang, Z. J. Wang, W. J. Yu, and J. Zhang, “Competitive swarm optimizer with dynamic grouping for large scale optimization,” in Proc. IEEE Congr. Evol. Comput. (CEC 2018), Rio de Janeiro, Brazil, Jul. 2018, pp. 2655-2660.[PDF]

  41. Y. F. Ge, W. J. Yu, Zhi-Hui Zhan(詹志辉), and J. Zhang, “Competition-based distributed differential evolution,” in Proc. IEEE Congr. Evol. Comput. (CEC 2018), Rio de Janeiro, Brazil, Jul. 2018, pp. 1-8.[PDF]

  42. R. D. Liu (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), W. N. Chen, Z. Yu, and J. Zhang, “Estimation of distribution algorithm for autonomous underwater vehicles path planning,” in Proc. Int. Symp. Neural Networks (ISNN 2018), Minsk, Belarus, Jun. 2018, pp. 647-655.[PDF]

  43. D. Liang (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “An adaptive ant colony system for public bicycle scheduling problem,” in Proc. 25th Int. Conf. Neural Information Processing (ICONIP 2018) , Angkor, Cambodia, Dec. 2018, pp. 417-429.[PDF]

  44. J. Wang, X. Chen, S. F. Sun, J. K. Liu, M. H. Au, and Zhi-Hui Zhan(詹志辉), “Towards efficient verifiable conjunctive keyword search for large encrypted database,” in Proc. European Symp. Research in Computer Security (ESORICS 2018), Barcelona, Spain, Sept. 2018, pp. 83-100.[PDF]

  45. S. Ye, Z. Yu, J. Lin, K. Yang, D. Dai, Zhi-Hui Zhan(詹志辉), W. N. Chen, and J. Zhang, “Two-dimensional-reduction random forest,” in Proc. Eighth Int. Conf. Info. Sci. and Techno. (ICIST 2018), Cordoba, Spain, Jun. 2018, pp. 145-152.[PDF]

    46. [2017]

  46. N. Ma, Xiao-Fang Liu (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), J. H. Zhong, and J. Zhang, “Load balance aware distributed differential evolution for computationally expensive optimization problems,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2017), Berlin, Germany, Jul. 2017, pp. 209-210.[PDF]

  47. Q. Z. Xiao, J. H. Zhong, W. N. Chen, Zhi-Hui Zhan(詹志辉), and J. Zhang, “Indicator-based multi-objective genetic programming for workflow scheduling problem,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2017), Berlin, Germany, Jul. 2017, pp. 217-218.[PDF]

  48. H. K. Zheng, J. J. Li, Y. J. Gong, W. N. Chen, Z. W. Yu, Zhi-Hui Zhan(詹志辉), and Y. Lin, “Link mapping-oriented ant colony system for virtual network embedding,” in Proc. IEEE Congr. Evol. Comput. (CEC 2017), San Sebastian, Spain, Jul. 2017, pp. 1223-1230.[PDF]

  49. Lin Shi (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), H. Q. Yuan, J. J. Li, and J. Zhang, “Distributed co-evolutionary particle swarm optimization using adaptive migration strategy,” in Proc. IEEE Symp. Series on Comput. Intell. (SSCI 2017), Hawaii, America, Nov. 2017, pp. 1-7.[PDF]

  50. Ting Huang (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), X. D. Jia, H. Q. Yuan, J. Q. Jiang, and J. Zhang, “Niching community based differential evolution for multimodal optimization problems,” in Proc. IEEE Symp. Series on Comput. Intell. (SSCI 2017), Hawaii, America, Nov. 2017, pp. 1-8.[PDF]

  51. Lin Shi (Student), Z. J. Wang, Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Experimental study of distributed differential evolution based on different platforms,” in Proc. Int. Conf. Bio-Inspired Computing: Theories and Applications (BIC-TA 2017), Harbin, China, Dec. 2017, pp. 476-486.[PDF]

  52. J. B. Wang, W. N. Chen, H. Cong, Zhi-Hui Zhan(詹志辉), and J. Zhang, “An ant colony system based virtual network embedding algorithm,” in Proc. IEEE Int. Conf. Syst., Man, and Cybern. (SMC 2017), Banff, Canada, Oct. 2017, pp. 1805-1810.[PDF]

  53. J. Chen, F. Alzami, Z. Yu, Zhi-Hui Zhan(詹志辉), and Q. Yang, “Soft subspace clustering ensemble framework based on the latent model,” in Proc. IEEE Int. Conf. Syst., Man, and Cybern. (SMC 2017), Banff, Canada, Oct. 2017, pp. 458-463.[PDF]

  54. J. Y. Ji, W. J. Yu, W. N. Chen, Zhi-Hui Zhan(詹志辉), and J. Zhang, “Solving multimodal optimization problems through a multiobjective optimization approach,” in Proc. Seventh Int. Conf. Info. Sci. and Techno. (ICIST 2017), Da Nang, Vietnam, April. 2017, pp. 2390-2395.[PDF]

    55. [2016]

  55. Xiao-Fang Liu (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), J. H. Lin, and J. Zhang, “Parallel differential evolution on distributed computational resources for power electronic circuit optimization,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2016), Denver, America, Jul. 2016, pp. 117-118.[PDF]

  56. Zhi-Hui Zhan(詹志辉), Z. J. Wang, Y. Lin, and J. Zhang, “Adaptive radius species based particle swarm optimization for multimodal optimization problems,” in Proc. IEEE Congr. Evol. Comput. (CEC 2016), Vancouver, Canada, Jul. 2016, pp. 2043-2048.[PDF]

  57. Zi-Jia Wang (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. J. Du, Z. W. Yu, and J. Zhang, “Orthogonal learning particle swarm optimization with variable relocation for dynamic optimization,” in Proc. IEEE Congr. Evol. Comput. (CEC 2016), Vancouver, Canada, Jul. 2016, pp. 594-600.[PDF]

  58. Zong-Gan Chen (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), W. Shi, W. N. Chen, and J. Zhang, “When neural network computation meets evolutionary computation: A survey,” in Proc. Int. Symp. Neural Networks (ISNN 2016), Saint Petersburg, Russia, Jul. 2016, pp. 603-612.[PDF]

  59. Zi-Jia Wang (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Parallel multi-strategy evolutionary algorithm using massage passing interface for many-objective optimization,” in Proc. IEEE Symp. Series on Comput. Intell. (SSCI 2016), Athens, Greece, Dec. 2016, pp. 1-8.[PDF]

  60. G. B. Chen, A. Song, C. J. Zhang, X. F. Liu, W. N. Chen, Zhi-Hui Zhan(詹志辉), J. H. Zhong, and J. Zhang, “Automatic clustering approach based on particle swarm optimization for data with arbitrary shaped clusters,” in Proc. Seventh Int. Conf. Intell. Control and Information Processing (ICICIP 2016), Angkor, Cambodia, Dec. 2016, pp. 41-48.[PDF]

  61. Q. Zou, S. X. Wan, B. Han, and Zhi-Hui Zhan(詹志辉), “BDSCyto: An automated approach for identifying cytokines based on best dimension searching,” in Proc.14th Pacific Rim Int. Conf. Artificial Intell. (PRICAI 2016), Phuket, Thailand, Aug. 2016, pp. 713-725.[PDF]

    62. [2015]

  62. Zhi-Hui Zhan(詹志辉) and J. Zhang, “Differential evolution for power electronic circuit optimization,” in Proc.Conf. Technologies and Applications of Artificial Intelligence (TAAI 2015), Tainan, Taiwan, Nov. 2015, pp. 158-163.[PDF]

  63. Xiao-Fang Liu (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Dichotomy guided based parameter adaptation for differential evolution,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2015), Madrid, Spain, Jul. 2015, pp. 289-296.[PDF]

  64. Hai-Hao Li (Student), Z. G. Chen (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. J. Du, and J. Zhang, “Renumber coevolutionary multiswarm particle swarm optimization for multi-objective workflow scheduling on cloud computing environment,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2015), Madrid, Spain, Jul. 2015, pp. 1419-1420.[PDF]

  65. Yan-Fei Li (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), Y. Lin, and J. Zhang, “Comparisons study of APSO OLPSO and CLPSO on CEC2005 and CEC2014 test suits,” in Proc. IEEE Congr. Evol. Comput. (CEC 2015), Sendai, Japan, May. 2015, pp. 3179-3185.[PDF]

  66. Zong-Gan Chen (Student), K. J. Du, Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Deadline constrained cloud computing resources scheduling for cost optimization based on dynamic objective genetic algorithm,” in Proc. IEEE Congr. Evol. Comput. (CEC 2015), Sendai, Japan, May. 2015, pp. 708-714.[PDF]

  67. Hai-Hao Li (Student), Y. W. Fu (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. J. Li, “Renumber strategy enhanced particle swarm optimization for cloud computing resource scheduling,” in Proc. IEEE Congr. Evol. Comput. (CEC 2015), Sendai, Japan, May. 2015, pp. 870-876.[PDF]

  68. Zong-Gan Chen (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), H. H. Li, K. J. Du, J. H. Zhong, Y. W. Foo, Y. Li, and J. Zhang, “Deadline constrained cloud computing resources scheduling through an ant colony system approach,” in Proc. Int. Conf. Cloud Computing Research and Innovation (ICCCRI 2015), Singapore, Oct. 2015, pp. 112-119.[PDF]

  69. Z. J. Wang (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “An improved method for comprehensive learning particle swarm optimization,” in Proc. IEEE Symp. Series on Comput. Intell. (SSCI 2015), Cape Town, South Africa, Dec. 2015, pp. 218-225.[PDF]

  70. Guang-Wei Zhang (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. J. Du, Y. Lin, W. N. Chen, J. J. Li, and J. Zhang, “Parallel particle swarm optimization using message passing interface,” in Proc. The 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2014&2015), vol. 1, pp. 55-64, 2015.[PDF]

  71. J. Z. Li, W. N. Chen, J. Zhang, and Zhi-Hui Zhan(詹志辉), “A parallel implementation of multiobjective particle swarm optimization algorithm based on decomposition,” in Proc. IEEE Symp. Series on Comput. Intell. (SSCI 2015), Cape Town, South Africa, Dec. 2015, pp. 1310-1317.[PDF]

  72. Y. W. Foo, C. Goh, H. C. Lim, Zhi-Hui Zhan(詹志辉), and Y. Li, “Evolutionary neural network based energy consumption forecast for cloud computing,” in Proc. Int. Conf. Cloud Computing Research and Innovation (ICCCRI 2015), Singapore, Oct. 2015, pp. 53-64.[PDF]

  73. A. Saldivar, Y. Li, W. Chen, Zhi-Hui Zhan(詹志辉), J. Zhang, and L. Chen, “Industry 4.0 with cyber-physical integration: A design and manufacture perspective,” in Proc. Int. Conf. Automation and Computing (ICAC 2015), Glasgow, UK, Sept. 2015, pp. 1-6.[PDF]

    74. [2014]

  74. Zhi-Hui Zhan(詹志辉), G. Y. Zhang, Y. Lin, Y. J. Gong, and J. Zhang, “Load balance aware genetic algorithm for task scheduling in cloud computing,” in Proc. Simulated Evolution And Learning (SEAL 2014), Dunedin, New Zealand, Dec. 2014, pp. 644-655.[PDF]

  75. Meng-Dan Zhang (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), J. J. Li, and J. Zhang, “Tournament selection based artificial bee colony algorithm with elitist strategy,” in Proc. Conf. Technologies and Applications of Artificial Intelligence (TAAI 2014) , Taiwan, Nov. 2014. pp. 387-396.[PDF]

  76. Guang-Wei Zhang (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. J. Du, and W. N. Chen, “Normalization group brain storm optimization for power electronic circuit optimization,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2014), Vancouver, Canada, Jul.. 2014, pp. 183-184.[PDF]

  77. Xiao-Fang Liu (Student), Zhi-Hui Zhan(詹志辉)(Corresponding Author), K. J. Du, and W. N. Chen, “Energy aware virtual machine placement scheduling in cloud computing based on ant colony optimization approach,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2014), Vancouver, Canada, Jul.. 2014, pp. 41-47.[PDF]

  78. Zhi-Hui Zhan(詹志辉), J. J. Li, and J. Zhang, “Adaptive particle swarm optimization with variable relocation for dynamic optimization problems,” in Proc. IEEE Congr. Evol. Comput. (CEC 2014), Beijing, China, Jul. 2014, pp. 1565-1570.[PDF]

  79. H. F. Li (Student), Y. J. Gong, Zhi-Hui Zhan(詹志辉), W. N. Chen, and J. Zhang, “Pseudo multi-population differential evolution for multimodal optimization,” in Proc. 10th Int. Conf. Natural Computation (ICNC 2014), Xiamen, China, Aug. 2014, pp. 457-462.[PDF]

  80. Y. H. Zhang, Y. J. Gong, W. N. Chen, Zhi-Hui Zhan(詹志辉), and J. Zhang, “A generic archive technique for enhancing the niching performance of evolutionary computation,” in Proc. IEEE Symp. Series on Comput. Intell. (SSCI 2014), Orlando, America, Dec. 2014, pp. 1-8.[PDF]

    81. [2013]

  81. Zhi-Hui Zhan(詹志辉), W. N. Chen, Y. Lin, Y. J. Gong, Y. L. Li, and J. Zhang, “Parameter investigation in brain storm optimization,” in Proc. IEEE Symp. Series on Comput. Intell. (SSCI 2013), Singapore, April. 2013, pp. 103-110.[PDF]

  82. Y. L. Li, and Zhi-Hui Zhan(詹志辉)(Corresponding Author), and J. Zhang, “Differential evolution enhanced with evolution path vector,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2013) , Amsterdam, The Netherlands, Jul., 2013, pp. 123-124.[PDF]

  83. X. M. Hu, Zhi-Hui Zhan(詹志辉), Y. Lin, Y. J. Gong, W. J. Yu, Y. X. Hu, and J. Zhang, “Multiobjective genetic algorithm for demand side management of smart grid,” in Proc. IEEE Symp. Series on Comput. Intell. (SSCI 2013), Singapore, April. 2013, pp. 14-21.[PDF]

  84. Y. Liu, W. N. Chen, Zhi-Hui Zhan(詹志辉), Y. Lin, Y. J. Gong, and J. Zhang, “A set-based discrete differential evolution algorithm,” in Proc. IEEE Conf. Syst. Man, and Cybern. (SMC 2013) , Manchester, UK, Oct. 2013, pp. 1347-1352.[PDF]

  85. J. Wu, Y. Lin, Zhi-Hui Zhan(詹志辉), W. N. Chen, Y. B. Lin, and J. Chen, “An ant colony optimization approach for nurse rostering problem,” in Proc. IEEE Conf. Syst. Man, and Cybern. (SMC 2013), Manchester, UK, Oct. 2013, pp. 1672-1676.[PDF]

    86. [2012]

  86. Zhi-Hui Zhan(詹志辉), J. Zhang, K. J. Du, and J. Xiao, “Extended binary particle swarm optimization approach for disjoint set covers problem in wireless sensor networks,” in Proc.Conf. Technologies and Applications of Artificial Intelligence (TAAI 2012), Taipei, Taiwan, Nov. 2012, pp. 327-331.[PDF]

  87. Zhi-Hui Zhan(詹志辉), J. Zhang, Y. H. Shi, and H. L. Liu, “A modified brain storm optimization,” in Proc. IEEE Congr. Evol. Comput. (CEC 2012), Brisbane, Australia, Jun. 2012, pp. 1-8.[PDF]

  88. Zhi-Hui Zhan(詹志辉), and J. Zhang, “Enhance differential evolution with random walk,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2012), Philadelphia, America, Jul. 2012, pp. 1513-1514.[PDF]

    89. [2011]

  89. Zhi-Hui Zhan(詹志辉), and J. Zhang, “Co-evolutionary differential evolution with dynamic population size and adaptive migration strategy,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2011), Dublin, Ireland, Jul., 2011, pp. 211-212.[PDF]

  90. Zhi-Hui Zhan(詹志辉), and J. Zhang, “Orthogonal learning particle swarm optimization for power electronic circuit optimization with free search range,” in Proc. IEEE Congr. Evol. Comput. (CEC 2011), New Orleans, America, Jun., 2011, pp.2563-2570.[PDF]

    91. [2010]

  91. Zhi-Hui Zhan(詹志辉) and J. Zhang, “Self-adaptive differential evolution based on PSO learning strategy,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2010), Portland, America, Jul., 2010, pp. 39-46.[PDF]

  92. Zhi-Hui Zhan(詹志辉) and J. Zhang, “A parallel particle swarm optimization approach for multiobjective optimization problems,” in Proc. ACM Genetic Evol. Comput. Conf.(GECCO 2010), Portland, America, Jul., 2010, PP. 81-82.[PDF]

  93. Zhi-Hui Zhan(詹志辉), J. Zhang, and Z. Fan, “Solving the optimal coverage problem in wireless sensor networks using evolutionary computation algorithms,” in Proc. of the 8th Int. Conf. Simulated Evolution and Learning (SEAL 2010), Kanpur, India, Dec., 2010, pp. 166–176.[PDF]

  94. Zhi-Hui Zhan(詹志辉), J. Zhang, and Y. H. Shi, “Experimental study on PSO diversity,” in Proc. 3rd Int. Workshop on Advanced Comput. Intell. (IWACI 2010), Suzhou, China, Aug., 2010, pp. 310-317.[PDF]

  95. N. Chen, Zhi-Hui Zhan(詹志辉), J. Zhang, O. Liu, and H. L. Liu, “A genetic algorithm for the optimization of admission scheduling strategy in hospitals,” in Proc. IEEE Congr. Evol. Comput. (CEC 2010), Barcelona, Spain, Jul. 2010, pp. 1-5.[PDF]

    96. [2009]

  96. Zhi-Hui Zhan(詹志辉), J. Zhang, and R. Z. Huang, “Particle swarm optimization with information share mechanism,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2009), Montréal, Canada, Jul., 2009, pp. 1761-1762.[PDF]

  97. Zhi-Hui Zhan(詹志辉), J. Zhang, and O. Liu, “Orthogonal learning particle swarm optimization,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2009), Montréal, Canada, Jul., 2009, pp. 1763-1764.[PDF]

  98. Zhi-Hui Zhan(詹志辉), J. Zhang, and Y. J. Gong, “Ant colony system based on receding horizon control for aircraft arrival sequencing and scheduling,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2009), Montréal, Canada, Jul., 2009, pp. 1765-1766.[PDF]

  99. Zhi-Hui Zhan(詹志辉), X. L. Feng, Y. J. Gong, and J. Zhang, “Solving the flight frequency programming problem with particle swarm optimization,” in Proc. IEEE Congr. Evol. Comput. (CEC 2009), Trondheim, Norway, May., 2009, pp. 1383-1390.[PDF]

  100. Zhi-Hui Zhan(詹志辉) and J. Zhang, “Parallel particle swarm optimization with adaptive asynchronous migration strategy,” The 9th Int. Conf. Algorithms and Architectures for Parallel Processing (ICA3PP 2009), Taipei, Taiwan, Jun., 2009, pp. 490-501.[PDF]

  101. Zhi-Hui Zhan(詹志辉) and J. Zhang, “Discrete particle swarm optimization for multiple destination routing problems,” in Proc. European Workshops on the Applications of Evolutionary Computation (EVA 2009), LNCS 5484, Tubingen, Germany, April, 2009, pp. 117–122.[PDF]

    102. [2008]

  102. Zhi-Hui Zhan(詹志辉) and J. Zhang, “Adaptive particle swarm optimization,” in Proc. Int. Conf. Ant Colony Optimization and Swarm Intelligence (ANTS 2008), Brussels, Belgium, Sept. 2008, pp. 227-234.[PDF]

  103. J. Zhang, Y. Shi, and Zhi-Hui Zhan(詹志辉), “Power electronic circuits design: A particle swarm optimization approach,” in Proc. of Int. Conf. on Simulated Evolution and Learning (SEAL 2008), Melbourne, Australia, Dec. 2008, pp. 605-614.[PDF]

    104. [2007]

  104. Zhi-Hui Zhan(詹志辉), J. Xiao, J. Zhang, and W. N. Chen, “Adaptive control of acceleration coefficients for particle swarm optimization based on clustering analysis,” in Proc. IEEE Congr. Evol. Comput. (CEC 2007), Singapore, Sept. 2007, pp. 3276-3282.[PDF]

Technique Books

  1. Book Chapter: Zhi-Hui Zhan(詹志辉) and J. Zhang, “Bio-Inspired Computation for Solving the Optimal Coverage Problem in Wireless Sensor Networks: A Binary Particle Swarm Optimization Approach,” Bio-Inspired Computation in Telecommunications, Morgan Kaufmann, pp. 263-285, Feb. 2015. [PDF]

  2. J. Zhang, Zhi-Hui Zhan, W. N. Chen, J. H. Zhong, N. Chen, Y. J. Gong, R. T. Xu, and Z. Guan, Computation Intelligence, Tsinghua University Press, November, 2009.
    张军（导师）, 詹志辉，陈伟能，钟竞辉，陈霓，龚月姣，许瑞填，官兆 编著，《计算智能》，清华大学出版社，2009年11月。

  3. J. Zhang, W. N. Chen, X. M. Hu, Y. Lin, W. L. Zhong, Zhi-Hui Zhan, and T. Huang, Numerical Computing，Tsinghua University Press, July, 2008.
    张军（导师）, 陈伟能，胡晓敏，林盈，钟文亮，詹志辉，黄韬 编著，《数值计算》，清华大学出版社，2008 年7月。

Authorized Patents授权专利

  1. 詹志辉、王子佳、张军，基于头脑风暴算法的功率电子电路优化方法及其应用，专利号：ZL 202010927568.3，申请日：2020-09-07，授权日：2022-09-20，证书号：5468666

  2. 詹志辉、张欣、张军，基于多蚁群系统的多目标供应链配置方法，专利号：ZL202010285488.2，申请日：2020-04-13，授权日：2022-07-26，证书号：5337835

  3. 詹志辉、吴丽娇，基于蚁群优化算法的智慧城市动态冷链物流调度方法，专利号：ZL202110263136.1，申请日：2021-03-11，授权日：2022-06-14，证书号：5233253

  4. 詹志辉、邓壮杰，基于多榜样学习粒子群的智慧城市信号灯配时优化方法，专利号：ZL202110271046.7，申请日：2021-03-11，授权日：2022-03-29，证书号：5034591

  5. 张军、詹志辉、龚月姣、张鑫源，基于差分进化算法的优化无线传感器网络寿命方法，专利号：ZL201711274875.0，申请日：2017-12-06，授权日：2020-12-22，证书号：4165931

  6. 张军、詹志辉、黄韬， 基于粒子群算法的多播路由方法，专利号：ZL200810220650.1，申请日：2008-12-31，授权日：2011-07-20，证书号：812987

  7. 张军、龚月姣、詹志辉、林盈、周淑姿，利用差分进化算法优化Iaas两目标任务调度的方法，专利号：ZL201811194822.2，申请日：2018-10-15，授权日：2021-09-21，证书号：4693035

  8. 张军、龚月姣、詹志辉、林盈，一种功率电子电路优化方法，专利号：ZL201811337985.1，申请日：2018-11-12，授权日：2021-07-20，证书号：4563849

  9. 张军、龚月姣、詹志辉、林盈，一种无线传感网络中无线传感器调度优化方法，专利号：ZL201910077495.0，申请日：2019-12-28，授权日：2020-08-18，证书号：3942435

  10. 张军、陈伟能、詹志辉，运用基于重用策略的智能群体算法优化动态旅行商问题的方法，专利号：ZL201711275295.3，申请日：2017-12-06，授权日：2021-07-20，证书号：4563333

  11. 陈伟能、谈力滔、詹志辉、钟竞辉，一种运用蚁群算法优化科学工作流的虚拟机放置方法，专利号：ZL202011311324.9，申请日：2020-11-20，授权日：2023-01-06，证书号：5684093

  12. 龚月姣、赵森华、黄婷、詹志辉，一种行程规划方法及系统，专利号：202010071853.X，申请日：2020-01-21，授权日：2022-04-22，证书号：5101164

  13. 陈伟能、姜春瑶、龚月姣、詹志辉，一种基于交通流预测的城市交通信号控制系统，专利号：ZL 202011306672.7，申请日：2020-11-20，授权日：2022-09-20，证书号：5467087


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