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In Press

  • Z. Zhang, Y. Wang, G. Sun, and T. Pang. A distribution information-based Kriging-assisted evolutionary algorithm for expensive many-objective optimization problems. IEEE Transactions on Evolutionary Computation, in press.
  • J. Liu, Y. Wang, G. Sun, and T. Pang. Constrained evolutionary Bayesian optimization for expensive constrained optimization problems with inequality constraints. IEEE Transactions on Systems, Man and Cybernetics: Systems, in press.
  • B.-C. Wang, Z.-D. Ji, Y. Wang, H.-X. Li, and Z. Li. A physics-informed composite network for modeling of electrochemical process of large-scale lithium-ion batteries. IEEE Transactions on Industrial Informatics, in press.
  • B.-C. Wang, C.-L. Dai, Y. Wang, and H.-X. Li. Time/space separation-based physics-informed machine learning for spatiotemporal modeling of distributed parameter systems. IEEE Transactions on Systems, Man and Cybernetics: Systems, in press.
  • Z. Zhang, Y. Wang, G. Sun, T. Pang, and K. Tang. Constrained probabilistic Pareto dominance for expensive constrained multiobjective optimization problems. IEEE Transactions on Evolutionary Computation, in press.
  • S. Tan, Y. Wang, G. Sun, T. Pang, and K. Tang. A surrogate-assisted evolutionary framework for expensive multitask optimization problems. IEEE Transactions on Evolutionary Computation, in press.

    • 2024

  • Y. Wang, Y. Zhou, and P.-Q. Huang. A novel incentive mechanism for federated learning over wireless communications. IEEE Transactions on Artificial Intelligence, vol. 5, no. 11, pp. 5561-5574, 2024.
  • S. Jiang, J. Guo, Y. Wang, and S. Yang. Evolutionary multi/many-objective optimisation via bilevel decomposition. IEEE/CAA Journal of Automatica Sinica, vol. 11, no. 9, pp. 1974-1987, 2024.
  • B.-C. Wang, Y.-Y. Mao, Y. Wang, and H.-X. Li. Gaussian process-accelerated multiobjective evolutionary design of charging process considering multiple user preferences. IEEE Transactions on Industrial Informatics, vol. 20, no. 8, pp. 10123-10133, 2024.
  • Z. Zhang, Y. Wang, J. Liu, G. Sun, and K. Tang. A two-phase Kriging-assisted evolutionary algorithm for expensive constrained multiobjective optimization problems. IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 54, no. 8, pp. 4579-4591, 2024.
  • F. Yao, Y. Chen, L. Wang, Z. Chang, P.-Q. Huang, and Y. Wang. A bilevel evolutionary algorithm for large-scale multiobjective task scheduling in multiagile earth observation satellite systems. IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 54, no. 6, pp. 3512-3524, 2024.
  • T. Zhang, X. Tong, and Y. Wang. Semantics-assisted multiview fusion for SAR automatic target recognition. IEEE Geoscience and Remote Sensing Letters, vol. 21, pp. 1-5, 2024, Art no. 4007005.
  • Q. Li and Y. Wang. Self-supervised pretraining based on noise-free motion reconstruction and semantic-aware contrastive learning for human motion prediction. IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 8, no. 1, pp. 738-751, 2024.
  • J. Xu, Y. Wang, X. He, and Y. Zou. Support-query mutual promotion and classification correction network for few-shot object detection. IEEE Signal Processing Letters, vol. 31, pp. 201-205, 2024.
  • X. Tong and Y. Wang. Active multiview fusion framework for SAR automatic target recognition. IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-14, 2024, Art no. 2504814.
  • Q. Li, Y. Wang, and F. Lv. Semantic correlation attention-based multiorder multiscale feature fusion network for human motion prediction. IEEE Transactions on Cybernetics, vol. 54, no. 2, pp. 825-838, 2024.
  • Z. Li, Y. Wang, and K. Li. FewVS: A vision-semantics integration framework for few-shot image classification. Proceedings of the 32st ACM International Conference on Multimedia (MM'24), 2024, in press.

    • 2023

  • P.-Q. Huang, Q. Zhang, and Y. Wang. Bilevel optimization via collaborations among lower-level optimization tasks. IEEE Transactions on Evolutionary Computation, vol. 27, no. 6, pp. 1837-1850, 2023. 
  • J. Liu, Y. Wang, G. Sun, and T. Pang. Solving highly expensive optimization problems via evolutionary expected improvement. IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 53, no. 8, pp. 4843-4855, 2023.
  • P.-Q. Huang, Y. Wang, K. Wang, and Q. Zhang. Combining Lyapunov optimization with evolutionary transfer optimization for long-term energy minimization in IRS-aided communications. IEEE Transactions on Cybernetics, vol. 53, no. 4, pp. 2647-2657, 2023.
  • Z. Ma and Y. Wang. Shift-based penalty for evolutionary constrained multiobjective optimization and its application. IEEE Transactions on Cybernetics, vol. 53, no. 1, pp. 18-30, 2023. [pdf] [code]
  • Z.-Y. Shui, X.-H. Li, Y. Feng, B.-C. Wang, and Y. Wang. Combining reduced-order model with data-driven model for parameter estimation of Lithium-ion battery. IEEE Transactions on Industrial Electronics, vol. 70, no. 2, pp. 1521-1531, 2023.
  • X. He, Y. Wang, S. Zhao, and X. Chen, Co-attention fusion network for multimodal skin cancer diagnosis, Pattern Recognition, vol. 133, Article 108990, 2023.
  • Y. Wang, L. Zhong, W. Huang, and X. He. An edge-assisted computing and mask attention based network for lung region segmentation. International Journal of Intelligent Systems, vol. 2023, Article 8589867, 2023.
  • X. He, Y. Wang, S. Zhao, and X. Chen. Joint segmentation and classification of skin lesions via a multi-task learning convolutional neural networt. Expert Systems with Applications, vol. 230, Article 120174, 2023.
  • Z. Li and Y. Wang. Better integrating vision and semantics for improving few-shot classification. Proceedings of the 31st ACM International Conference on Multimedia (MM'23), 2023, pp. 4737-4746.

    • 2022

  • J. Liu, Y. Wang, P.-Q. Huang, and S. Jiang. CaR: A cutting and repulsion-based evolutionary framework for mixed-integer programming problems. IEEE Transactions on Cybernetics, vol. 52, no. 12, pp. 13129-13141, 2022. [pdf]
  • P.-Q. Huang, Y. Wang, and K. Wang. A divide-and-conquer bilevel optimization algorithm for jointly pricing computing resources and energy in wireless powered MEC. IEEE Transactions on Cybernetics, vol. 52, no. 11, pp. 12099-12111, 2022. [pdf]
  • J. Liu, Y. Wang, G. Sun, and T. Pang. Multisurrogate-assisted ant colony optimization for expensive optimization problems with continuous and categorical variables. IEEE Transactions on Cybernetics, vol. 52, no. 11, pp. 11348-11361, 2022.  [pdf] We no longer provide the source code of this paper.
  • Y. Wang, J. Lin, J. Liu, G. Sun, and T. Pang. Surrogate-assisted differential evolution with region division for expensive optimization problems with discontinuous responses. IEEE Transactions on Evolutionary Computation, vol. 26, no. 4, pp. 780-792, 2022. [pdf] We no longer provide the source code of this paper.
  • J. Liu, Y. Wang, B. Xin, and L. Wang. A biobjective perspective for mixed-integer programming. IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 52, no. 4, pp. 2374-2385, 2022. [pdf] [code]
  • Y. Wang, S. He, and B.-C. Wang. Evolutionary sensor placement for spatiotemporal modeling of battery thermal process. IEEE Transactions on Industrial Informatics, vol. 18, no. 4, pp. 2223-2232, 2022.
  • Y. Wang, T. Xue, and Q. Li. A robust image sequence-based framework for visual place recognition in changing environments. IEEE Transactions on Cybernetics, vol. 52, no. 1, pp. 152-163, 2022. [pdf] [code]
  • Q. Li and Y. Wang. A novel teacher-assistance-based method to detect and handle bad training demonstrations in learning from demonstration. IEEE Transactions on Cognitive and Developmental Systems, vol. 14, no. 3, pp. 948-956, 2022. [pdf] [video]
  • S. Hu, B. Lei, S. Wang, Y. Wang, Z. Feng, and Y. Shen. Bidirectional mapping generative adversarial networks for brain MR to PET synthesis. IEEE Transactions on Medical Imaging, vol. 41, no. 1, pp. 145-157, 2022.
  • X. He, Y. Wang, S. Zhao, and C. Yao. Deep metric attention learning for skin lesion classification in dermoscopy images. Complex & Intelligent Systems, vol. 8, no. 2, pp. 1487-1504, 2022.

    • 2021

  • Z.-Z. Liu, Y. Wang, B.-C. Wang. Indicator-based constrained multiobjective evolutionary algorithms. IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 51, no. 9, pp. 5414-5426, 2021. [pdf] [code]
  • Z. Ma, Y. Wang, and W. Song. A new fitness function with two rankings for evolutionary constrained multiobjective optimization. IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 51, no. 8, pp. 5005-5016, 2021.  [pdf] [code]
  • B.-C. Wang, H.-X. Li, Q. Zhang, and Y. Wang. Decomposition-based multiobjective optimization for constrained evolutionary optimization. IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 51, no. 1, pp. 574-587, 2021. [pdf] [code]
  • X. He, Y. Wang, X. Wang, W. Huang, S. Zhao, and X. Chen. Simple-encoded evolving convolutional neural network and its application to skin disease image classification. Swarm and Evolutionary Computation, vol. 67, Article 100955, 2021
  • Y. Wang, C. Chen, P.-Q. Huang, and K. Wang. A new differential evolution algorithm for joint mining decision and resource allocation in a MEC-enabled wireless blockchain network. Computers & Industrial Engineering, vol. 155, Article 107186, 2021. [pdf] [code]

    • 2020

  • P.-Q. Huang and Y. Wang. A framework for scalable bilevel optimization: Identifying and utilizing the interactions between upper-level and lower-level variables. IEEE Transactions on Evolutionary Computation, vol. 24, no. 6, pp. 1150-1163, 2020. [pdf] [code]
  • M. Asim, Y. Wang, K. Wang, and P.-Q. Huang. A review on computational intelligence techniques in cloud and edge computing. IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 4, no. 6, pp. 742-763, 2020. [pdf]
  • P.-Q. Huang, Y. Wang, K. Wang, and Z.-Z. Liu. A bilevel optimization approach for joint offloading decision and resource allocation in cooperative mobile edge computing. IEEE Transactions on Cybernetics, vol. 50, no. 10, pp. 4228-4241, 2020. [pdf] [code]
  • Y. Wang, Z.-Y. Ru, K. Wang, and P.-Q. Huang. Joint deployment and task scheduling optimization for large-scale mobile users in multi-UAV enabled mobile edge computing. IEEE Transactions on Cybernetics, vol. 50, no. 9, pp. 3984-3997, 2020. [pdf] [code]
  • Y. Wang, J.-P. Li, X. Xue, and B.-C. Wang. Utilizing the correlation between constraints and objective function for constrained evolutionary optimization. IEEE Transactions on Evolutionary Computation, vol. 24, no. 1, pp. 29-43, 2020. [pdf] [code]
  • Y. Wang, X. Xue, and B. Chen. Matsuoka's CPG with desired rhythmic signals for adaptive walking of humanoid robots. IEEE Transactions on Cybernetics, vol. 50, no. 2, pp. 613-626, 2020. [pdf] [video]
  • W. Gong, Y. Wang, Z. Cai, and L. Wang. Finding multiple roots of nonlinear equation systems via a repulsion-based adaptive differential evolution. IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 50, no. 4, pp. 1499-1513, 2020. [pdf] [code]
  • P.-Q. Huang, Y. Wang, K. Wang, and K. Yang. Differential evolution with a variable population size for deployment optimization in a UAV-assisted IoT data collection system. IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 4, no. 3, pp. 324-335, 2020. [pdf] [code]
  • Z.-Z. Liu, Y. Wang, and P.-Q. Huang. AnD: A many-objective evolutionary algorithm with angle-based selection and shift-based density estimation. Information Sciences, vol. 509, pp. 400-419, 2020. [pdf] [code]
  • P. Tan, X. Wang, and Y. Wang. Dimensionality reduction in evolutionary algorithms-based feature selection for motor imagery brain-computer interface. Swarm and Evolutionary Computation, vol. 52, Article 100597, 2020. [pdf] [code]
  • P.-Q. Huang, Y. Wang, and K. Wang. Energy-efficient trajectory planning for a multi-UAV-assisted mobile edge computing system. Frontiers of Information Technology & Electronic Engineering, vol. 21, no. 12, pp.1713-1725, 2020. [pdf] [code]
  • Y. Li, Z. Wu, S. Zhao, X. Wu, Y. Kuang, Y. Yan, S. Ge, K. Wang, W. Fan, X. Chen, and Y. Wang. PSENet: Psoriasis severity evaluation network. Proceedings of Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), February 7-12, 2020, New York, USA. [pdf]
  • S. Jiang, Y. Wang, M. Kaiser, and N. Krasnogor. NIHBA: a network interdiction approach for metabolic engineering design. Bioinformatics, vol. 36, no. 11, pp. 3482-3492, 2020. Please contact Dr. Shouyong Jiang for the source code.

    • 2019

  • Z. Ma and Y. Wang. Evolutionary constrained multiobjective optimization: Test suite construction and performance comparisons. IEEE Transactions on Evolutionary Computation, vol. 23, no. 6, pp. 972-986, 2019. [pdf] [code]
  • Z.-Z. Liu and Y. Wang. Handling constrained multiobjective optimization problems with constraints in both the decision and objective spaces. IEEE Transactions on Evolutionary Computation, vol. 23, no. 5, pp. 870-884, 2019. [pdf] [code]
  • Y. Wang, D.-Q. Yin, S. Yang, and G. Sun. Global and local surrogate-assisted differential evolution for expensive constrained optimization problems with inequality constraints. IEEE Transactions on Cybernetics, vol. 49, no. 5, pp. 1642-1656, 2019. [code] [PlatEMO]
  • Z.-Z. Liu, Y. Wang, S. Yang, and K. Tang. An adaptive framework to tune the coordinate systems in nature-inspired optimization algorithms. IEEE Transactions on Cybernetics, vol. 49, no. 4, pp. 1403-1416. 2019. [pdf] [code]
  • B.-C. Wang, H.-X. Li, J.-P. Li, and Y. Wang. Composite differential evolution for constrained evolutionary optimization. IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 49, no. 7, pp. 1482-1495, 2019. [pdf] [code]
  • Y. Wang, J. Yu, S. Yang, S. Jiang, and S. Zhao. Evolutionary dynamic constrained optimization: Test suite construction and algorithm comparisons. Swarm and Evolutionary Computation, vol. 50, Article 100559, 2019. [pdf] [code]

    • 2018

  • Y. Wang, H. Liu, H. Long, Z. Zhang, and S. Yang. Differential evolution with a new encoding mechanism for optimizing wind farm layout. IEEE Transactions on Industrial Informatics, vol. 14, no. 3, pp. 1040-1054, 2018. [pdf] [code]
  • Z.-Z. Liu, J.-W. Huang, Y. Wang, and D. Cao. ECoFFeS: A software using evolutionary computation for feature selection in drug discovery. IEEE Access, vol. 6, pp. 20950-20963, 2018. The Matlab source code can be downloaded from: https://github.com/JiaweiHuang/ECoFFeS
  • S. Jiang, S. Yang, Y. Wang, and X. Liu. Scalarizing functions in decomposition-based multiobjective evolutionary algorithms. IEEE Transactions on Evolutionary Computation, vol. 22, no. 2, pp. 296-313, 2018. Please contact Dr. Shouyong Jiang for the source code.
  • Y. Wang, Z.-Z. Liu, J. Li, H.-X. Li, and J. Wang. On the selection of solutions for mutation in differential evolution. Frontiers of Computer Science, vol. 12, no. 2, pp. 297-315, 2018. [pdf]

    • 2017

  • Y. Wang, B. Xu, G. Sun, and S. Yang. A two-phase differential evolution for uniform designs in constrained experimental domains. IEEE Transactions on Evolutionary Computation, vol. 21, no. 5, pp. 665-680, 2017. [pdf] [code]
  • W. Gong, Y. Wang, Z. Cai, and S. Yang. A weighted biobjective transformation technique for locating multiple optimal solutions of nonlinear equation systems. IEEE Transactions on Evolutionary Computation, vol. 21, no. 5, pp. 697-713, 2017. [pdf] [code]

    • 2016

  • Y. Wang, B.-C. Wang, H.-X. Li, and G. G. Yen. Incorporating objective function information into the feasibility rule for constrained evolutionary optimization. IEEE Transactions on Cybernetics, vol. 46, no. 12, pp. 2938-2952, 2016. [pdf] [code]
  • Y. Wang, Z.-Z. Liu, J. Li, H.-X. Li, and G. G. Yen. Utilizing cumulative population distribution information in differential evolution. Applied Soft Computing, vol. 48, pp. 329-346, 2016. [pdf] [code]
  • J.-P. Li, Y. Wang, S. Yang, and Z. Cai. A comparative study of constraint-handling techniques in evolutionary constrained multiobjective optimization. 2016 IEEE Congress on Evolutionary Computation (CEC), Vancouver, BC, 2016, pp. 4175-4182. [pdf] [code]
  • J. Wang, Y. Zhou, Y. Wang, J. Zhang, C. L. P. Chen, and Z. Zheng. Multiobjective vehicle routing problems with simultaneous delivery and pickup and time windows: Formulation, instances, and algorithms. IEEE Transactions on Cybernetics, vol. 46, no. 3, pp. 582-594, 2016. Please contact Prof. Jiahai Wang for the source code.

    • 2015

  • W. Song, Y. Wang, H.-X. Li, and Z. Cai. Locating multiple optimal solutions of nonlinear equation systems based on multiobjective optimization. IEEE Transactions on Evolutionary Computation, vol. 19, no. 3, pp. 414-431, 2015. [pdf] [code]
  • Y. Wang, H.-X. Li, G. G. Yen, and W. Song. MOMMOP: Multiobjective optimization for locating multiple optimal solutions of multimodal optimization problems. IEEE Transactions on Cybernetics, vol. 45, no. 4, pp. 830-843, 2015. [pdf] [code]
  • Y. Wang, J.-J. Huang, N. Zhou, D.-S. Cao, J. Dong, and H.-X. Li. Incorporating PLS model information into particle swarm optimization for descriptor selection in QSAR/QSPR. Journal of Chemometrics, vol. 29, no. 12, pp. 627–636, 2015. [code]
  • Y. Zhou, J. Zhang, and Y. Wang. Performance analysis of the (1+1) evolutionary algorithm for the multiprocessor scheduling problem. Algorithmica, vol. 73, no. 1, pp. 21-41, 2015.

    • 2014

  • Y. Wang, H.-X. Li, T. Huang, and L. Li. Differential evolution based on covariance matrix learning and bimodal distribution parameter setting. Applied Soft Computing, vol. 18, pp. 232-247, 2014. [pdf] [code]

    • 2013

  • G. Jia, Y. Wang, Z. Cai, and Y. Jin. An improved (μ+λ)-constrained differential evolution for constrained optimization. Information Sciences, vol. 222, pp. 302-322, 2013. [code]

    • 2012

  • Y. Wang and Z. Cai. Combining multiobjective optimization with differential evolution to solve constrained optimization problems. IEEE Transactions on Evolutionary Computation, vol. 16, no. 1, pp. 117-134, 2012. [code]
  • Y. Wang and Z. Cai. A dynamic hybrid framework for constrained evolutionary optimization. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 42, no. 1, pp. 203-217, 2012. [code]
  • Y. Wang, Z. Cai, and Q. Zhang. Enhancing the search ability of differential evolution through orthogonal crossover. Information Sciences, vol. 185, no. 1, pp. 153-177, 2012. [code]
  • Y. Wang, J. Xiang, and Z. Cai. A regularity model-based multiobjective estimation of distribution algorithm with reducing redundant cluster operator. Applied Soft Computing, vol. 12, no. 11, pp. 3526-3538, 2012. [code]

    • 2011

  • Y. Wang, Z. Cai, and Q. Zhang. Differential evolution with composite trial vector generation strategies and control parameters. IEEE Transactions on Evolutionary Computation, vol. 15, no. 1, pp. 55-66, 2011. [code]
  • Y. Wang and Z. Cai. Constrained evolutionary optimization by means of (μ+λ)-differential evolution and improved adaptive trade-off model. Evolutionary Computation, vol. 19, no. 2, pp. 249-285, 2011. [code]

    • 2010

  • H. Liu, Z. Cai, and Y. Wang. Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization. Applied Soft Computing, vol. 10, no. 2, pp. 629-640, 2010. [code]

    • 2009

  • Y. Wang, Z. Cai, and Y. Zhou. Accelerating adaptive trade-off model using shrinking space technique for constrained evolutionary optimization. International Journal for Numerical Methods in Engineering, vol. 77, no. 11, pp. 1501-1534, 2009. [code]
  • Y. Wang, Z. Cai, Y. Zhou, and Z. Fan. Constrained optimization based on hybrid evolutionary algorithm and adaptive constraint-handling technique. Structural and Multidisciplinary Optimization, vol. 37, no. 1, pp. 395-413, 2009. [code]
  • Y. Wang and Z. Cai. A hybrid multi-swarm particle swarm optimization to solve constrained optimization problems. Frontiers of Computer Science in China, vol. 3, no. 1, pp. 38-52, 2009. [code]

    • 2008

  • Y. Wang, Z. Cai, Y. Zhou, and W. Zeng. An adaptive tradeoff model for constrained evolutionary optimization. IEEE Transactions on Evolutionary Computation, vol. 12, no. 1, pp. 80-92, 2008. [code]

    • 2007

  • Y. Wang, Z. Cai, G. Guo, and Y. Zhou. Multiobjective optimization and hybrid evolutionary algorithm to solve constrained optimization problems. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 37, no. 3, pp. 560-575, 2007. [code]
  • Y. Wang, H. Liu, Z. Cai, and Y. Zhou. An orthogonal design based constrained evolutionary optimization algorithm. Engineering Optimization, vol. 39, no. 6, pp. 715-736, 2007. [code]

    • 2006

  • Z. Cai and Y. Wang. A multiobjective optimization-based evolutionary algorithm for constrained optimization. IEEE Transactions on Evolutionary Computation, vol. 10, no. 6, pp. 658-675, 2006. [code]

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