爱游戏体育平台赞助意甲优惠活动

赵宏，博士，2020年毕业于华南理工大学计算机科学与工程爱游戏体育平台赞助意甲优惠活动，师从IEEE Fellow詹志辉教授，专注于人工智能优化算法及其应用的研究。2021年加入爱游戏体育平台赞助意甲优惠活动万人领军人才刘静教授团队，是团队的骨干成员，致力于科学研究与成果转化，主持8项科研项目，包括爱游戏体育平台赞助意甲优惠活动自然科学基金、广州市重点研发项目、广东省面上基金和广东省青年基金等。

在多AGV智能调度与优化领域开展了深入的实践研究，为复杂工厂环境下的优化问题提供了有效的解决方案，其设计的调度算法已成功实现商用落地。此外，在2021年新进教师中得到了爱游戏体育平台赞助意甲优惠活动“优秀学员”称号，在2022年华为发布的ADN自动驾驶网络难题中荣获“火花奖”。自2023年起，担任智能感知与计算师生联合党支部书记，并主讲本科生课程《人工智能导论》和研究生课程《算法设计与分析》。

截至目前，已指导硕士研究生30名，其中15人已毕业，5人获得校级优秀毕业生称号如爱游戏体育平台赞助意甲优惠活动。所在团队近年来承担和参与了多项爱游戏体育平台赞助意甲优惠活动级重要科研项目，“973”、“863”如发表了一系列高水平学术论文。这些成果已在顶级国际期刊和会议上发表，计划、爱游戏体育平台赞助意甲优惠活动科技支撑计划、爱游戏体育平台赞助意甲优惠活动发展与改革委员会示范工程以及爱游戏体育平台赞助意甲优惠活动自然科学基金重点项目等，IEEE Transactions on Evolutionary Computation、IEEE Transactions on Cybernetics、计算机学报及International Symposium on Neural Networks，授权爱游戏体育平台赞助意甲优惠活动发明专利累计发表高水平论文30余篇，15项，其中2项已成功转化。

积极参加国际学术交流活动，曾在IEEE Congress on Evolutionary Computation (CEC 2020)、Genetic and Evolutionary Computation Conference 2022 (GECCO’22) 和 GECCO’24上进行口头成果汇报。还受邀担任ICACI 2021程序委员会委员和中国计算机学会协同计算专委会委员，并被多个国际著名期刊邀请为审稿人。如

• IEEE Transactions on Evolutionary Computation (IF=11.7／2024, 中科院一区,计算智能领域顶级期刊)

• IEEE Transactions on Cybernetics (IF=9.4/2024, 中科院一区,计算智能领域顶级期刊)

 2021年1月入职以来，已经获批项目8项，作为技术负责人参与项目4项，其中爱游戏体育平台赞助意甲优惠活动自然科学基金1项，省级项目3项，地市级项目2项，横向项目6项，部分信息如下：

• 爱游戏体育平台赞助意甲优惠活动自然科学基金-青年项目 2024-2026年

• 广州市重点研发项目 2022-2025年

• 广东省自然科学基金-面上项目 2022-2025年

• 区域联合基金-青年基金项目 2021-2024年

• 广州市博士青年科技项目 2021-2024年 

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• 招生信息：每年5个硕士招生名额和2个博士招生名额

• 基本要求：要求爱游戏体育平台赞助意甲优惠活动热爱科研、勤奋刻苦、服从团队管理
  

• 欢迎对智能计算、智能调度、进化优化、复杂网络优化、和机器爱游戏体育平台赞助意甲优惠活动等研究方向感兴趣的同学加入我们！

• 可通过邮件与我联系：hongzhao@ xidian.edu.cn
  

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已发表论文

[1] Min Liang, Hong Zhao*, Jian-Yu Li, PEBCC: A Pre-evolution-based Cooperative Co-evolution Algorithm for Large-scale Optimization, Applied Soft Computing, Accept, 2026.06.

[2] KeXin Liu, Hong Zhao*, Yi-Fan Li, Multi-scale Multi-objective Evolutionary Neural Architecture Search Considering Model Generalization for SDN Performance Prediction, Applied Soft Computing, Accept. 2026.05.

[3] Hong Zhao, Ling Tang, LiGuang Xie, Jing Liu, KMoPSOTE: Advancing Self-Driving Networks with a Knowledge-Driven Multi-Objective Particle Swarm Optimization Algorithm for Traffic Engineering，IEEE Transactions on Evolutionary Computation, Accept, 2026.4.

[4] Wei Zeng, Hong Zhao*, JianYu Li, Jing Liu, “Bi-Learning Evolutionary Optimization with Substructure Preservation for the Capacitated Vehicle Routing Problem ”, IEEE Transactions on Evolutionary Computation, Accept, 2025.12.11.

[5] Hong Zhao (赵宏), Xu-Hui Ning, Jing Liu, "Evolutionary Multitask Framework With Bi-Knowledge Transfer for Multimodal Optimization Problems," in IEEE Transactions on Evolutionary Computation, vol. 30, no. 1, pp. 393-407, Feb. 2026, (中科院一区top，IF/2024=11.7, 计算智能领域顶级期刊)

[6] Hong Zhao (赵宏), Zhi-Hui Zhan, et. al., “Local Binary Pattern Based Adaptive Differential Evolution for Multimodal Optimization Problems,” IEEE Transactions on Cybernetics, vol. 50, no. 7, pp. 3343-3357, July 2020. (中科院一区, IF/2023=11.8, 在计算机-控制领域23本国际期刊中排名第一)

[7] Hong Zhao, HaoNan Huang, ZhiYa Cui, Jing Liu, “Multiagent Reinforcement Learning Aided Multiobjective Evolutionary Algorithm With Local Higher-Order Information for Community Detection,” IEEE Transactions on Computational Social Systems, doi: 10.1109/TCSS.2025. 3606954. 2025.9.

[8] 赵宏, 李珈瑞, 刘静, “基于局部时空的多峰优化算法及其在PID控制中的应用”, 计算机学报, vol. 47, no. 6, pp. 1323-1340, 2024. (一级学会期刊)

[9] HaoNang Huang, Hong Zhao* (赵宏), and Jing Liu, “MOMC3D: A Novel Multiobjective Optimization Method With Mixed-Coding Strategy for Standard Cells in Chip 3-D Placement,” in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 44, no. 12, pp. 4444-4457, Dec. 2025. (CCF A 类期刊)

[10] YiFan Li, Hong Zhao*, Jian-Yu Li, Jing Liu, “Multimodal Multiobjective Neural Architecture Search for Lightweight and Failure-Resilient Time Series Forecasting,” IEEE Transactions on Evolutionary Computation, doi: 10.1109/TEVC.2026.3658547, 2026.1. (中科院一区top，IF/2024=11.7, 计算智能领域顶级期刊)

[11] Hong Zhao, Ling Tang, Jia-Rui Li, Zong-Gan Chen, A Key Node Detection Method Assisted by Multi-layer Surrogate Model and Multi-dimensional Network Features in Complex Networks, Applied soft computing, 2026.2. Accepted.

[12] Hong Zhao (赵宏), Jing Liu, “Differential Evolution with Outlier-based Selection Approach for Multimodal Optimization Problems,” Applied Soft Computing, vol. 140, 110264, 2023. (中科院一区，IF/2023=8.7)

[13] Hong Zhao (赵宏), Ling Tang, Jing Liu, “Strengthen Evolution-based Differential Evolution with Prediction Strategy for Multimodal Optimization and Its Application in Multirobot Task Allocation”, Applied Soft Computing, vol. 139, 110218, 2023. (中科院一区，IF/2023=8.7)

[14] Hong Zhao(赵宏), XuHui Ning, XiaoTao Liu, Chao Wang, Jing Liu, “What makes Evolutionary Multi-Task Optimization better: A Comprehensive Survey”, Applied Soft Computing, vol. 110545, 156849, 2023. (中科院一区，IF/2023=8.7)

[15] XiangQian Li, Hong Zhao*(赵宏), Jing Liu, “Minimum Spanning Tree Niching-based Differential Evolution with Knowledge-Driven Update Strategy for Multimodal Optimization Problems”, Applied Soft Computing, vol. 145, 110589, 2023. (中科院一区，IF/2024=7.2)

[16] Tao Ma, Hong Zhao*(赵宏), Jing Liu, “Coarse- and Fine-grained Combined Clustering-based Differential Evolution for Multimodal Optimization Problems and Its Application in Multirobot Task Allocation”, Swarm and Evolutionary Computation, vol. 83, 101412, 2023. (中科院一区，IF/2024=8.2)

[17] Tao Ma, Hong Zhao*(赵宏), Xiangqian Li, Fang Yang, Chun-sheng Liu, Jing Liu, Reinforcement learning assisted differential evolution with adaptive resource allocation strategy for multimodal optimization problems, Swarm and Evolutionary Computation, Volume 94, 2025, 101888.

[18] Tao Ma, Li Guang Xie, Hong Zhao*(赵宏), Fang Yang, Chunsheng Liu, Jing Liu, A novel decision-making agent-based multi-objective automobile insurance pricing algorithm with insurers and customers satisfaction, Information Sciences, Volume 693, 2025, 121665.

[19] Tao Ma, Hong Zhao*(赵宏), Ling Tang, Mingsheng Xue,, and Jing Liu, Efficient Black-Box Attack with Surrogate Models and Multiple Universal Adversarial Perturbations, Scientific Reports, Accept, 2025.1.

[20] Xiyuan Chen, Hong Zhao*(赵宏), Jing Liu, “A Network Community-based Differential Evolution for Multimodal Optimization Problems”, Information Science. vol. 645, 119359, 2023. (IF/2023=8.1)

[21] Hong Zhao (赵宏), Zhi-Hui Zhan, et. al.,” Multiple Populations Co-evolutionary Particle Swarm Optimization for Multi-objective Cardinality Constrained Portfolio Optimization Problem,” Neurocomputing, vol. 430, pp. 58-70, 2021. (中科院二区，IF/2024=5.5)

[22] ZhiYa Cui, Hong Zhao, Jing Liu, Multi-level Learning-aided Co-evolutionary Particle Swarm Optimization algorithm for Multi-objective Fuzzy Flexible Job Shop Scheduling Problem, （SR） Accept, 2025.9.

[23] Hong Zhao (赵宏), Jia Rui Li, and Jing Liu. “Localized Distance and Time-Based Differential Evolution for Multimodal Optimization Problems,” In Proceedings of the Genetic and Evolutionary Computation Conference 2022 (GECCO’22). ACM, New York. (IEEE旗舰国际会议，CCF C类)

[24] Jiang Zhu, Hong Zhao*, He Yu, and Jing Liu. 2024. Pixel Logo Attack: Embedding Attacks as Logo-Like Pixels. In Genetic and Evolutionary Computation Conference (GECCO ’24), July 14–18, 2024, Melbourne, VIC, Australia. ACM .(IEEE旗舰国际会议, CCF C类)

[25] Xuhui Ning, Hong Zhao*(赵宏), Xiaotao Liu, Jing Liu, “An Evolutionary Multi-Task Genetic Algorithm with Assisted-task for Flexible Job Shop Scheduling” Chinese CSCW 2022, accepted. （协同计算专委会议）

[26] Hong Zhao , Xiangqian Li, Jing Liu, “A Reachability-distance based Differential Evolution with Individual Transfer for Multimodal Optimization Problems,” in Proc. IEEE Congress on Evolutionary Computation, 1-8，2023.4. (IEEE旗舰国际会议)

[27] Hong Zhao, Zhi-Hui Zhan, et. al., “Adaptive Guidance-based Differential Evolution with Archive Strategy for Multimodal Optimization Problems,” in Proc. IEEE Congress on Evolutionary Computation, Glasgow, UK, pp. 1-8, Jul. 2020. (IEEE旗舰国际会议)

[28] Hong Zhao , Zhi-Hui Zhan, et. al., “An Improved Selection Operator for Multi-Objective Optimization,” in Proc. International Symposium on Neural Networks (ISNN 2019), Moscow, Russia, Jul. 2019, pp. 379-388. (神经网络旗舰国际会议)

[29] Shihao Yuan, Hong Zhao, Jing Liu, “Self-organizing Map Based Differential Evolution with Dynamic Selection Strategy for Multimodal Optimization Problems”, Mathematical Biosciences and Engineering, vol. 19, no. 6, pp. 5968-5997, 2022.

[30] Hong Zhao , Zhi-Hui Zhan, et. al., “A Multi-angle Hierarchical Differential Evolution Approach for Multimodal Optimization Problems”，IEEE Access, vol. 8, pp. 178322-178335, 2020.

已授权专利

 [1] 赵宏, 刘洋, 刘静, “基于智能预测和误差识别的多AGV规划方法及系统,” 专利号：202111644827.2, 已转让, 2022. (通过该专利的技术转化显著缩短了物料搬运的时间，加快了整个生产线的速度，提高整体生产效率)

[2] 赵宏, 袁锴薪, 刘静, “面向复杂环境的带实时冲突消解的多AGV智能协同调度方法,” 专利号：202110958806.1，已转让， 2023. (通过该项技术的转化有效避免多AGV之间的碰撞和堵塞，保证各AGV在复杂环境下的顺畅运行，从而提高整个系统的作业效率)

[3] 赵宏, 袁锴薪, 刘静, “一种基于蚁群优化算法的多AGV动态路径规划方法”, 已授权, 2023111894420, 2023.12.

[4] 赵宏, 李相前, 刘静, “基于遗传算法的分布式全流程作业车间调度方法及终端”, 已授权, 202310880659X, 2023.12.

[5] 赵宏,李艺帆, 刘静等 “一种大规模软件定义网络性能预测方法” , 已授权, 2023 1 0127510.4, 2023.10.

[6] 刘静, 李艺帆, 赵宏等 “一种基于密母神经架构搜索的软件定义网络性能预测方法”, 已授权, 2023 10127530.1, 2023.11.

[7] 赵宏, 唐凌, 刘静, “一种基于双层优化的大规模集成电路布局优化方法”, 已授权, 202211282004.4, 2023.4.

[8] 赵宏, 陈文玮,刘静, “基于遗传算法的大规模集成电路布局优化方法”, 已授权, 202211367045.3, 2023.4.

[9] 赵宏, 薛明胜, 刘静, “基于多重普遍对抗扰动的黑盒对抗样本生成方法、装置”, 已授权, 2024106610334, 2024.5.

[10] 赵宏, 谢礼光, 刘静, “一种应用于汽车保险定价的多目标优化方法及终端”,已授权, 202311868143X, 2023.12.

[11] 刘静, 陈玺元, 赵宏, “ 一种基于滑动窗口和离散差分进化算法的3D布局优化方法”, 已授权, 202211632016.5, 2023.8.

[12] 赵宏,刘洋,刘静,袁锴薪，基于进化算法的电镀线行车调度方法、装置及存储介质，已授权，2021 1 0826240.7，2025.3.

 

团队名称：人工智能团队