Journal papers: (after joining SUSTech)

[1] Qiang He, Lihong Sun, Xingwei Wang*, Zhenkun Wang, Min Huang, Bo Yi, Yuantian Wang, and Lianbo Ma. Positive opinion maximization in signed social networks. Information Sciences, 558: 34-49, 2021. (INS, IF 8.1)

[2] Hui-Ling Zhen, Zhenkun Wang*, Xijun Li, Qingfu Zhang, Mingxuan Yuan, and Jia Zeng. Accelerate the optimization of large-scale manufacturing planning using game theory. Complex & Intelligent Systems, 8(4): 2719-2730, 2022 (CAIS, IF 5.8)

[3] Qite Yang, Zhenkun Wang*, Jianping Luo, and Qiang He. Balancing performance between the decision space and the objective space in multimodal multiobjective optimization. Memetic Computing, 13(1): 31-47, 2021. (MC, IF 4.7)

[4] Zhenkun Wang*, Hui-Ling Zhen, Jingda Deng, Qingfu Zhang, Xijun Li, Mingxuan Yuan, and Jia Zeng. Multiobjective optimization-aided decision-making system for large-scale manufacturing planning. IEEE Transactions on Cybernetics, 52(8): 8326-8339, 2022. (TCYB, IF 11.8)

[5] Weijing Dai,  Zhenkun Wang*, and Ke Xue. System-in-package design using multi-task memetic learning and optimization. Memetic Computing, 14(1): 45-59, 2022. (MC, IF 4.7)

[6] Zhenkun Wang*,  Qingyan Li, Qite Yang,  and Hisao Ishibuchi. The dilemma between eliminating dominance resistant solutions and preserving boundary solutions of extremely convex Pareto fronts. Complex & Intelligent Systems, 9: 1117–1126, 2023. (CAIS, IF 5.8)

[7] Genghui Li, Qingfu Zhang*, and Zhenkun Wang*. Evolutionary competitive multitasking optimization. IEEE Transactions on Evolutionary Computation, 26(2): 278-289, 2022. (TEVC, IF 14.3)

[8] Zhenkun Wang*,  Qingfu Zhang, Yew-Soon Ong, Shunyu Yao, Haitao Liu, and Jianping Luo. Choose appropriate subproblems for collaborative modeling in expensive multiobjective optimization. IEEE Transactions on Cybernetics, 53(1): 483-496, 2023. (TCYB, IF 11.8)

[9] 高卫峰, 刘玲玲, 王振坤, 公茂果. 基于分解的演化多目标优化算法综述. 软件学报,  34 (10), 4743-4771, 2023.

[10] Zhongju Yuan†,  Genghui Li†, Zhenkun Wang*, Jianyong Sun, and Ran Cheng. RL-CSL: A combinatorial optimization method using reinforcement learning and contrastive self-supervised learning. IEEE Transactions on Emerging Topics in Computational Intelligence, 7(4): 1010-1024, 2023. (TETCI, IF 5.3)

[11] Lei Cao, Chunming Ye, Ran Cheng*, and Zhenkun Wang. Memory-based variable neighborhood search for green vehicle routing problem with passing-by drivers: A comprehensive perspective. Complex & Intelligent Systems, 8(3): 2507-2525, 2023. (CAIS, IF 5.8)

[12] Genghui Li, Zhenkun Wang*, Qingfu Zhang, and Jianyong Sun. Offline and online objective reduction via Gaussian mixture model clustering. IEEE Transactions on Evolutionary Computation, 27(2): 341-354, 2023. (TEVC, IF 14.3)

[13] Wencheng Han, Hao Li*, Maoguo Gong*, Jianzhao Li, Yiting Liu, and Zhenkun Wang, Multi-swarm particle swarm optimization based on CUDA for sparse reconstruction. Swarm and Evolutionary Computation, 75: 101153, 2022. (SWEVO, IF 10.0)

[14] Zhenkun Wang†, Shuangchun Gui†, Xingpeng Ding, Xiaowei Hu*, Xiaowei Xu*, and Xiaomeng Li. Spectrum and style transformation framework for omni-domain COVID-19 diagnosis. IEEE Transactions on Emerging Topics in Computational Intelligence, 7(5): 1527-1538, 2023. (TETCI, IF 5.3)

[15] Genghui Li, Zhenkun Wang*, and Maoguo Gong. Expensive optimization via surrogate-assisted and model-free evolutionary optimization. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 53(5): 2758-2769, 2023. (TSMCA, IF 8.7)

[16] Xin Liu, Jianyong Sun*, Qingfu Zhang, Zhenkun Wang, and Zongben Xu. Learning to learn evolutionary algorithm: A learnable differential evolution. IEEE Transactions on Emerging Topics in Computational Intelligence, 7(6): 1605-1620, 2023. (TETCI, IF 5.3)

[17] Jixiang Chen, Fu Luo, Genghui Li, and Zhenkun Wang*. Batch Bayesian optimization with adaptive batch acquisition functions via multi-objective optimization. Swarm and Evolutionary Computation, 79: 101293, 2023. (SWEVO, IF 10.0)

[18] Genghui Li†, Lindong Xie†, Zhenkun Wang*, Huajun Wang, and Maoguo Gong. Evolutionary algorithm with individual-distribution search strategy and regression-classification surrogates for expensive optimization. Information Sciences, 634: 423-442, 2023. (INS, IF 8.1)

[19] Jiaqian Li†, Genghui Li†, Zhenkun Wang, and Laizhong Cui*. Differential evolution with an adaptive penalty coefficient mechanism and a search history exploitation mechanism. Expert Systems with Applications, 230: 120530, 2023. (ESWA, IF 8.5)

[20] Huajun Wang*, Genghui Li, and Zhenkun Wang. Fast SVM classifier for large-scale classification problems. Information Sciences, 642: 119136, 2023. (INS, IF 8.1)

[21] Genghui Li, Zhenkun Wang*, Jianyong Sun, and Qingfu Zhang. Objective extraction for simplifying many-objective solution sets. IEEE Transactions on Emerging Topics in Computational Intelligence, 8(1): 337-349, 2024. (TETCI, IF 5.3)

[22] Lindong Xie†, Genghui Li†, Zhenkun Wang*, Laizhong Cui, and Maoguo Gong. Surrogate-assisted evolutionary algorithm with model and infill criterion auto-configuration. IEEE Transactions on Evolutionary Computation, in press, 2023. (TEVC, IF 14.3)

[23] Nwoye C I, Yu T, Sharma S, et al.. CholecTriplet2022: Show me a tool and tell me the triplet - an endoscopic vision challenge for surgical action triplet detection. Medical Image Analysis, 89: 102888, 2023. (MIA, IF 10.9)

[24] Zhenkun Wang*,  Shunyu Yao, Genghui Li, and Qingfu Zhang. Multi-objective combinatorial optimization using a single deep reinforcement learning model. IEEE Transactions on Cybernetics, 54(3): 1984-1996, 2024. (TCYB, IF 11.8)

[25] Zhi Zheng†, Shunyu Yao†, Genghui Li, Linxi Han, and Zhenkun Wang*. Pareto improver: Learning improvement heuristics for multi-objective route planning. IEEE Transactions on Intelligent Transportation Systems, 25(1): 1033-1043, 2024. (TITS, IF 8.5)

[26] Zhenkun Wang*†, Qingyan Li†, Genghui Li, and Qingfu Zhang. Multi-objective decomposition evolutionary algorithm with objective modification-based dominance and external archive. Applied Soft Computing, 149: 111006, 2023. (ASOC, IF 8.7)

[27] Shuangchun Gui, Zhenkun Wang*, Jixiang Chen, Xun Zhou, Chen Zhang, and Yi Chao. MT4MTL-KD: A multi-teacher knowledge distillation framework for triplet recognition. IEEE Transactions on Medical Imaging, in press, 43(4): 1628-1639, 2024. (TMI, IF 10.6)

[28] Han Li†, Genghui Li†, Qiaoyong Jiang, Jiashu Wang, and Zhenkun Wang*. MOEA/D with customized replacement neighborhood and dynamic resource allocation for solving 3L-SDHVRP.  Swarm and Evolutionary Computation, 85: 101143, 2024. (SWEVO, IF 10.0)

[29] Xun Zhou, Zhenkun Wang*, Liang Feng*, Songbai Liu, Ka-Chun Wong, and Kay Chen Tan. Towards evolutionary multi-task convolutional neural architecture search. IEEE Transactions on Evolutionary Computation, in press, 2024. (TEVC, IF 14.3)

[30] Xiangzhou Gao, Shenmin Song*, Hu Zhang, and Zhenkun Wang. A Flexible Ranking-Based Competitive Swarm Optimizer for Large-Scale Continuous Multi-Objective Optimization. IEEE Transactions on Evolutionary Computation, in press, 2024. (TEVC, IF 14.3)

[31] Genghui Li, Zhenkun Wang*, Weifeng Gao, and Ling Wang. Decoupling constraint: Task clone-based multi-tasking optimization for constrained multi-objective optimization. IEEE Transactions on Evolutionary Computation, in press, 2024. (TEVC, IF 14.3)

[32] Wen Zou, Zhanxin Cui, Genghui Li*, Zhiwei Feng, Zhenkun Wang, Qingyu Gao, Qingbin Zhang, Tao Yang. Reentry capsule reachable tube boundary prediction via evolutionary multiobjective optimization. International Journal of Aerospace Engineering, in press, 2024. (IJAE, IF 1.4)

[33] Ruihao Zheng†, Yin Wu†, Genghui Li, Yu Zhang, and Zhenkun Wang*. Decomposition with adaptive composite norm for evolutionary multi-objective combinatorial optimization.  Swarm and Evolutionary Computation, in press, 2024. (SWEVO, IF 10.0)

[34] Zhengjun Wang, Weifeng Gao*, Genghui Li*, Zhenkun Wang, Maoguo Gong. Path planning for unmanned aerial vehicle via off-policy reinforcement learning with enhanced exploration. IEEE Transactions on Emerging Topics in Computational Intelligence, in press, 2024. (TETCI, IF 5.3)

[35] Kangnian Lin, Genghui Li, Qingyan Li, Zhenkun Wang*, Hisao Ishibuchi, Hu Zhang. Multi-objective evolutionary algorithm with evolutionary-status-driven environmental selection. Information Sciences, 669: 120551, 2024. (INS, IF 8.1)

Conference papers: (after joining SUSTech)

[1] Qite Yang, Zhenkun Wang*, Hisao Ishibuchi. It Is Hard to Distinguish Between Dominance Resistant Solutions and Extremely Convex Pareto Optimal Solutions. The 11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021, Shenzhen, China, March 28–31, 2021.

[2] Zhenkun Wang, Jingda Deng*, Qingfu Zhang, Qite Yang. On the Parameter Setting of the Penalty-Based Boundary Intersection Method in MOEA/D. The 11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021, Shenzhen, China, March 28–31, 2021.

[3] Weijing Dai,  Zhenkun Wang, Ke Xue. Multi-objectives Design Optimization based on Multi-objectives Gaussian Processes for System-in-Package. IEEE 71st Electronic Components and Technology Conference, ECTC 2021, San Diego, California, United States, June 1–4, 2021.

[4] Jixiang Chen†, Fu Luo†, Zhenkun Wang*. Dynamic Multi-objective Ensemble of Acquisition Functions in Batch Bayesian Optimization. The Genetic and Evolutionary Computation Conference Companion, GECCO 2022,  Boston Massachusetts, United States, July 9-13, 2022.

[5] Genghui Li, Qingyan Li, Zhenkun Wang*. Adaptive Differential Evolution Algorithm with Multiple Gaussian Learning Models. The CAAI International Conference on Artificial Intelligence, CACAI 2022, Beijing, China, August 27-28, 2022.

[6] Ziliang Miao†, Buwei He†, Hubocheng Tang†, Jixiang Chen, Zhenkun Wang*. Stacked Ensemble of Metamodels for Expensive Global Optimization.  The 8th IEEE International Conference on Cloud Computing and Intelligence Systems, CCIS 2022, Chengdu, China, November 26-28, 2022.

[7] Ruihao Zheng, Zhenkun Wang*. A Generalized Scalarization Method for Evolutionary Multi-objective Optimization. Proceedings of the AAAI Conference on Artificial Intelligence, 37 (10), 12518-12525, AAAI-2023, Washington DC, United States, February 7-14, 2023. [Oral CCF-A]

[8] Yin Wu†, Ruihao Zheng†, Zhenkun Wang*. Decomposition-Based Multi-Objective Evolutionary Algorithm with Model-Based Ideal Point Estimation. Genetic and Evolutionary Computation Conference, GECCO 2023, Lisbon, Portugal, July 15-19, 2023. [Full paper CCF-C]

[9] Zhongju Yuan, Zhenkun Wang*, Genghui Li. Cross-Domain Few-Shot Relation Extraction via Representation Learning and Domain Adaptation. Genetic and Evolutionary Computation Conference, IJCNN 2023, Queensland, Australia, June 18-23, 2023. [CCF-C]

[10] Fu Luo†, Xi Lin†, Fei Liu, Qingfu Zhang, Zhenkun Wang*. Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization. The 37th Anniversary Conference on Neural Information Processing Systems, NeurIPS 2023, New Orleans, United States, December 10-16, 2023. [CCF-A]

[11] Lindong Xie, Kangnian Lin, Genghui Li*. Zhenkun Wang*. Dual-State-Driven Evolutionary Optimization for Expensive Optimization Problems with Continuous and Categorical Variables. The 5th International Conference on Data-driven Optimization of Complex Systems, DOCS 2023, Tianjin, China, September 22-24 2023.

[12] Rui Sun†, Zhi Zheng†, Zhenkun Wang*. Learning Encodings for Constructive Neural Combinatorial Optimization Needs to Regret. The 38th AAAI Conference on Artificial Intelligence (AAAI-24), Vancouver, Canada,  February 20-27, 2024. [CCF-A]

[13] Yunpeng Ba†, Ruihao Zheng†, Zhenkun Wang*. Decomposition-Based Memetic Algorithm for Multi-objective Fleet Size and Mix Vehicle Routing Problem. The 2024 IEEE Conference on Evolutionary Computation (IEEE CEC 2024), Pacifico Yokohama, Yokohama, Japan, 30 June - 5 July 2024.

[14] Keyu Zhou†, Jin Chen†, Shuangchun Gui*, Zhenkun Wang*. Towards Lightweight Underwater Depth Estimation, The 2024 IEEE Conference on Artificial Intelligence (IEEE CAI 2024). Marina Bay Sands, Singapore, June 25-27, 2024.

[15] Jun Huang†, Zongze Li†, Ruihao Zheng*, Zhenkun Wang*. UWM-Net: A Mixture Density Network Approach with Minimal Dataset Requirements for Underwater Image Enhancement. The 2024 IEEE Conference on Artificial Intelligence (IEEE CAI 2024), Marina Bay Sands, Singapore, June 25-27, 2024.

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Journal papers: (before joining SUSTech)

[1] Weifeng Gao*, Genghui Li, Qingfu Zhang, Yuting Luo, Zhenkun Wang, “Solving Nonlinear Equation Systems by a Two-Phase Evolutionary Algorithm”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51(9): 5652-5663, 2021. (TSMC, IF 8.7)

[2] Jianping Luo*, Xiongwen Huang, Yun Yang, Xia Li, Zhenkun Wang, Jiqiang Feng, “A Many-objective Particle Swarm Optimizer Based on Indicator and Direction Vectors for Many-objective Optimization”. Information Sciences, 514: 166-202, 2020. (INS, IF 8.1)

[3] Chen Xu, Yiyuan Chai, Sitian Qin, Zhenkun Wang, Jiqiang Feng*, “A Neurodynamic Approach to Nonsmooth Pseudoconvex Optimization Problems”, Neural Networks, 124: 180-192, 2020. (NN, IF 9.6)

[4] Hao Li, Yew-Soon Ong, Maoguo Gong*, Zhenkun Wang, “Evolutionary Multitasking Sparse Reconstruction: Framework and Case Study”, IEEE Transactions on Evolutionary Computation, 23(5): 733-747, 2019. (TEVC, IF 14.3)

[5] Jianping Luo*, Abhishek Gupta, Yew-Soon Ong, Zhenkun Wang, “Evolutionary Optimization of Expensive Multiobjective Problems with Co-sub-Pareto Front Gaussian Process Surrogates”, IEEE Transactions on Cybernetics, 49(5): 1708-1721, 2019. (TCYB, IF 11.8)

[6] Zhenkun Wang*, Yew-Soon Ong, Jianyong Sun*, Abhishek Gupta, Qingfu Zhang. “A Generator for Multiobjective Test Problems with Difficult-to-Approximate Pareto Front Boundaries”, IEEE Transactions on Evolutionary Computation, 23(4): 556-571, 2019. (TEVC, IF 14.3)

[7] Zhenkun Wang*, Yew-Soon Ong, Hisao Ishibuchi. “On Scalable Multiobjective Test Problems with Hardly-dominated Boundaries”, IEEE Transactions on Evolutionary Computation, 23(2): 217-231, 2019. (TEVC, IF 14.3)

[8] Zhenkun Wang*, Qingfu Zhang, Hui Li, Hisao Ishibuchi, Licheng Jiao, “On The Use of Two Reference Points in Decomposition Based Multiobjective Evolutionary Algorithms”, Swarm and Evolutionary Computation, 34: 89-102, 2017. (SWEVO, IF 10.0)

[9] Maoguo Gong*, Yue Wu, Qing Cai, Wenping Ma, Kai Qin, Zhenkun Wang, Licheng Jiao, “Discrete Particle Swarm Optimization for High-order Graph Matching”, Information Sciences, 328: 158-171, 2016. (INS, IF 8.1)

[10] Zhenkun Wang, Qingfu Zhang*, Aimin Zhou, Maoguo Gong, Licheng Jiao, Adaptive Replacement Strategies for MOEA/D, IEEE Transactions on Cybernetics, 46(2): 474-486, 2016. (TCYB, IF 11.8) [ESI highly cited paper]

Conference papers: (before joining SUSTech)

[1] Qingyu Tan, Zhenkun Wang, Yew-Soon Ong, Kin Huat Low*, “Evolutionary Optimization-based Mission Planning for UAS Traffic Management (UTM)”, 2019 International Conference on Unmanned Aircraft Systems, p. 952-958, (ICUAS) 2019.

[2] Mohamed Faisal B Mohamed Salleh, Wanchao Chi, Zhenkun Wang, Shuangyao Huang, Da-Yang Tan, Tingting Huang, Kin Huat Low*, “Preliminary Concept of Adaptive Urban Airspace Management for Unmanned Aircraft Operations” AIAA Information Systems-AIAA Infotech@ Aerospace p. 2260, (AIAA) 2018.

[3] Xingxing Hao, Jing Liu*, Zhenkun Wang, “An Improved Global Replacement Strategy for MOEA/D on Many-objective Knapsack Problems.” 2017 IEEE Congress on Automation Science and Engineering, p. 624-629, (CASE) 2017.

[4] Hiu-Hin Tam, Man-Fai Leung, Zhenkun Wang, Sin-Chun Ng, Chi-Chung Cheung, Andrew K Lui, "Improved Adaptive Global Replacement Scheme for MOEA/D-AGR", 2016 IEEE Congress on Evolutionary Computation, p. 2153-2160, (CEC) 2016.

[5] Zhenkun Wang*, Qingfu Zhang, Hui Li, “Balancing Convergence and Diversity by Using Two Different Reproduction Operators in MOEA/D: Some Preliminary Work”, 2015 IEEE Conference on Systems, Mans and Cybernetics, p. 2849–2854. (SMC) 2015.

[6] Zhenkun Wang*, Qingfu Zhang, Maoguo Gong, Aimin Zhou, “A Replacement Strategy for Balancing Convergence and Diversity in MOEA/D”, 2014 IEEE Congress on Evolutionary Computation, p. 2132-2139, (CEC) 2014.