**J. J. Liang**, P. N. Suganthan, A. K. Qin and S. Baska, Comprehensive learning particle swarm optimizer for global optimization of multimodal functions, *IEEE Transactions on Evolutionary Computation*, vol. 10(3), pp. 281-295, 2006. (**Highly cited**)

**J. J. Liang**, K. J. Qiao, K. J. Yu*, B. Y. Qu, C. T. Yue, W. F. Guo, L. Wang, Utilizing the relationship between unconstrained and constrained Pareto Fronts for constrained multi-Objective optimization, *IEEE Transactions on Cybernetics*, DOI: 10.1109/TCYB.2022.3163759, 2022.

**J. J. Liang**, X. X. Ban, K. J. Yu*, B. Y. Qu, K. J. Qiao, C. T. Yue, K. Chen, K. C. Tan, A survey on evolutionary constrained multi-objective optimization, *IEEE Transactions on Evolutionary Computation*, DOI: 10.1109/TEVC.2022.3155533, 2022.

**J. J. Liang**, H. Y. Lin, C. T. Yue*, K. J. Yu, Y. Guo, K. J. Qiao, Multiobjective Differential Evolution with Speciation for Constrained Multimodal Multiobjective Optimization, *IEEE Transactions on Evolutionary Computation*, 10.1109/TEVC.2022.3194253, 2022.

C. T. Yue, B. Y. Qu, and **J. J. Liang***, A multiobjective particle swarm optimizer using ring topology for solving multimodal multiobjective problems, *IEEE Transactions on Evolutionary Computation*, vol. 22, no. 5, pp. 805-817, 2018.(**ESI** **Highly cited**)

K. J. Qiao, K. J. Yu, B. Y. Qu, **J. J. Liang***, C. T. Yue, X. X. Ban. Feature Extraction for Recommendation of Constrained Multi-Objective Evolutionary Algorithms [J]. IEEE Transactions on Evolutionary Computation, DOI: 10.1109/TEVC.2022.3186667, 2022.

K. J. Qiao, K. J. Yu, B. Y. Qu, **J. J. Liang***, H. Song, C. T. Yue, H. Y. Lin, K. C. Tan, Dynamic auxiliary task-based evolutionary multitasking for constrained multi-objective optimization, *IEEE Transactions on Evolutionary Computation*, DOI: 10.1109/TEVC.2022.3175065, 2022.

K. J. Qiao, K. J. Yu, B. Y. Qu, **J. J. Liang***, H. Song, C. T. Yue, An evolutionary multitasking optimization framework for constrained multi-objective optimization problems, *IEEE Transactions on Evolutionary Computation*, 2022, 26(2): 263-277.

B. Y. Qu, P. N. Suganthan and** J. J. Liang**, Differential evolution with neighborhood mutation for multimodal optimization, *IEEE Transactions on Evolutionary Computation*, vol. 6, no. 5, pp. 601-614, 2012.

K. J. Yu, **J. J. Liang***, B. Y. Qu, Y. Luo, C. T. Yue, Dynamic selection preference-assisted constrained multiobjective differential evolution, *IEEE Transactions on Systems, Man, and Cybernetics: Systems*, vol. 52, no. 5, pp. 2954-2965, 2021.

K. J. Yu, **J. J. Liang***, B. Y. Qu, C. T. Yue, Purpose-directed two-phase multiobjective differential evolution for constrained multiobjective optimization, *Swarm and Evolutionary Computation*, vol. 60, no. 2021, pp.100799:1-14.

**J. J. Liang***, Y. P. Wei, B. Y. Qu, C. T. Yue, H. Song, Ensemble learning based on fitness Euclidean-distance ratio differential evolution for classification. *Natural Computing*, 2020:1-11.

X. J. Jia, **J. J. Liang**, K. Zhao, Z. L. Yang, M. Y. Yu, Multi-parameters optimization for electromagnetic acoustic transducers using surrogate-assisted particle swarm optimizer, *Mechanical Systems and Signal Processing*, vol. 152, no. 2021, pp.107337:1-18.

**J. J. Liang**, K. J. Qiao, C. T. Yue, K. J. Yu, B. Y. Qu, R. H. Xu, Z. M. Li, Y. Hu, A clustering-based differential evolution algorithm for solving multimodal multi-objective optimization problems, *Swarm and Evolutionary Computatio*n, vol. 60, no. 100788, 2020.

**J. J. Liang**, Guanlin Chen, Boyang Qu, Kunjie Yu*, Caitong Yue, Kangjia Qiao, Hua Qian*. "Cooperative co-evolutionary comprehensive learning particle swarm optimizer for formulation design of explosive simulant."* Memetic Computing*, 12 (2020): 331-341.

**J. J. Liang**, K. J. Qiao, K. J. Yu, S. L. Ge, B. Y. Qu, R. H. Xu, K. Li, Parameters estimation of solar photovoltaic models via a self-adaptive ensemble-base differential evolution, *Solar Energy*, 207(2020), pp.336-346.

**J. J. Liang**, K. J. Qiao, M. H. Yuan, K. J. Yu, B. Y. Qu, S. L. Ge, Y. X. Li and G. L. Chen, Evolutionary multi-task optimization for parameters extraction of photovoltaic models, *Energy Conversion and Management*, 207(2020), pp.1125901-15, 2020.

C. T. Yue, **J. J. Liang***, B. Y. Qu, Y. H. Han, Y. S. Zhu and O. D. Crisalle, A novel multiobjective optimization algorithm for sparse signal reconstruction,* Signal Processing*, vol. 167, no. 2020, pp.107292-107304, 2020.

C. T. Yue, B. Y. Qu, K. J. Yu, **J. J. Liang*** and X. D. Li, A novel scalable test problem suite for multimodal multiobjective optimization, *Swarm Evolutionary and Computation*. vol. 48, pp. 62-71, 2019.

K. J. Yu, B. Y. Qu, C. T. Yue, S. L. Ge, X. Chen and **J. J. Liang***, “A performance-guided JAYA algorithm for parameters identification of photovoltaic cell and module”, *Applied Energy*, vol. 237, no. 2019, pp. 241-257, 2019. (**ESI** **Highly cited**)

Y. Hu, J. Wang, **J. J. Liang***, K. J. Yu, H. Song, Q. Q. Guo, C. T. Yue and Y. L. Wang. A self-organizing multimodal multi-objective pigeon-inspired optimization algorithm, *SCIENCE CHINA Information Sciences*, 62(5), pp. 070206:1-070206:17, 2019.

**J. J. Liang**, S. Ge, B. Qu, K. Yu, F. Liu, H. Yang, P. Wei, and Z. Li, Classified perturbation mutation based particle swarm optimization algorithm for parameters extraction of photovoltaic models, *Energy Conversion and Management*, pp. 112138, 2019.(**ESI ****Highly cited**)

**J. J. Liang**, W. W. Xu, C. T. Yue, K. J. Yu, H. Song, O. C. Crisalle and B. Y. Qu*, Multimodal multiobjective optimization with differential evolution, *Swarm and Evolutionary Computation*, vol. 44, pp. 1028-1059, 2018.

K. J. Yu, **J. J. Liang***, B. Y. Qu, Z. P. Cheng and H. S. Wang, Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models, *Applied Energy*, vol. 226, no. 2018, pp. 408-422, 2018.(**ESI ****Highly cited**)

B. Y. Qu, Y. S. Zhu, Y. C. Jiao, M. Y. Wu, **J. J. Liang*** and P. N. Suganthan, A Survey on multi-objective evolutionary algorithms for the solution of the environmental/economic dispatch problems, *Swarm and Evolutionary Computation*, vol. 38, pp. 1-11, 2018.

K. J. Yu**, J. J. Liang***, B. Y. Qu, X. Chen and H. S. Wang, Parameters identification of photovoltaic models using an improved JAYA optimization algorithm, *Energy Conversion and Management*, vol. 150, pp. 742-753, 2017.(**ESI ****Highly cited**)

B. Y. Qu, **J. J. Liang***, Y. S. Zhu, Z. Y. Wang and P. N. Suganthan, Economic emission dispatch problems with stochastic wind power using summation based multi-objective evolutionary algorithm, *Information Sciences*, vol. 351, pp. 48-66, 2016.

B. Y. Qu, B. F. Lang, **J. J. Liang***, A. K. Qin and O. D. Crisalle, Two-hidden-layer extreme learning machine for regression and classification, *Neurocomputing*, vol. 175, pp. 826-834, 2016.

B. Y. Qu, **J. J. Liang***, Z. Y. Wang, Q. Chen and P. N. Suganthan, Novel benchmark functions for continuous multimodal optimization with comparative results, S*warm and Evolutionary Computation*, vol. 26, pp. 23-34, 2016.

**J. J. Liang**, B. Y. Qu, X. B. Mao, B. Niu and D.Y. Wang, Differential evolution based on fitness euclidean-distance ratio for multimodal optimization, *Neurocomputing*, vol. 137, pp. 252-260, 2014.

B. Y. Qu, **J. J. Liang** and** **P. N. Suganthan, Niching particle swarm optimization with local search for multi-modal optimization, *Information Sciences*, vol. 197, pp. 131-143, 2012.

**J. J. Liang**, C. C. Chan, P. N. Suganthan and V. L. Huang, Wavelength detection in FBG sensor network using tree search DMS-PSO, *IEEE Photonics Technology Letters*, vol. 18(12), pp. 1305 - 1307, 2006.

**Representative Conference Papers**

C. T. Yue, **J. J. Liang**, P. N. Suganthan, B. Y. Qu, K. J. Yu, and S. Liu, “MMOGA for Solving Multimodal Multiobjective Optimization Problems with Local Pareto Sets,” IEEE Congress on Evolutionary Computation, pp. 1-8, 2020.

**J. J. Liang**, P. Wei, B. Qu, K. Yu, C. Yue, Y. Hu and S. Ge, “Ensemble Learning Based on Multimodal Multiobjective Optimization,” Bio-Inspired Computing: Theories and Applications, pp. 299-313, 2019.

**J. J. Liang**, Z. Li and B. Qu, K. Yu, K. Qiao and S. Ge “A Knee Point based NSGA-II Multi-objective Evolutionary Algorithm” Bio-Inspired Computing: Theories and Applications, pp. 454-467, 2019.

**J. J. Liang**, Y. Li, B. Qu, K. Yu and Y. Hu, “Mutation Strategy Selection Based on Fitness Landscape Analysis: A Preliminary Study,” Bio-Inspired Computing: Theories and Applications, pp. 284-298, 2019.

**J. J. Liang**, H. T. Yang, W. T. Sun, J. J. Gao, “PSO-based CNN for Keyword Selection on Google Ads,” IEEE Congress on Evolutionary Computation, pp. 562-569, 2019.

C. T. Yue, **J. J. Liang**, B. Y. Qu, K. J. Yu, and H. Song, “Multimodal Multiobjective Optimization in Feature Selection,” IEEE Congress on Evolutionary Computation, pp. 302-309, 2019.

**J. J. Liang**, P. Wang, C. T. Yue, K. J. Yu, Z. H. Li, B. Y. Qu, Multi-objective Brainstorm Optimization Algorithm for Sparse Optimization. IEEE Congress on Evolutionary Computation, pp. 1-8, 2018.

**J. J. Liang**, X. P. Zhu, C. T. Yue, Z. H. Li, B. Y. Qu, Performance Analysis on Knee Point Selection Methods for Multi-Objective Sparse Optimization Problems. IEEE Congress on Evolutionary Computation, pp. 2507-2514, 2018.

**J. J. Liang**, Q. Q. Guo, C. T. Yue, B. Y. Qu and K. J. Yu, “A Self-Organizing Multi-Objective Particle Swarm Optimization Algorithm for Multimodal Multi-Objective Problems”, International Conference on Swarm Intelligence, pp. 550-560, 2018.

C. T. Yue, **J. J. Liang**, B. Y. Qu, Z. P. Lu, B. L. Li, and Y. H. Han, “Sparse Representation Feature for Facial Expression Recognition”, International Conference on Extreme Learning Machines, pp. 12-21, 2017.

M. Y. Yu, **J. J. Liang**, B. Y. Qu, and C. T. Yue, “Optimization of UWB Antenna Based on Particle Swarm Optimization Algorithm”, International Symposium on Intelligence Computation and Applications, pp. 86-97, 2017.

**J. J. Liang**, M. Y. Yu,C. T. Yue, M. M. Li, and Z. X. Yue, “Routing Algorithm Based on SPSO, Advanced Information Technology”, Electronic and Automation Control Conference, pp. 1350-1354, 2017

B. L. Li, **J. J. Liang**, C. T. Yue, and B. Y. Qu, “Multivariant Optimization Algorithm with Bimodal-gauss”, International Conference on Simulated Evolution and Learning 2017,pp. 920-92, 2017

C. T. Yue, **J. J. Liang**, B. Y. Qu, H. Song, G. Li, and Y. H. Han, “A Knee Point Driven Particle Swarm Optimization Algorithm for Sparse Reconstruction”, International Conference on Simulated Evolution and Learning 2017, pp. 911-919, 2017

**J. J. Lian**g, C. T. Yue, and B. Y. Qu, “Multimodal multi-objective optimization: A preliminary study”, IEEE Congress on Evolutionary Computation 2016, pp. 2454-2461, 2016.

**J. J. Liang**, L. Guo, R. Liu and B.Y. Qu, “A Self-adaptive Dynamic Particle Swarm Optimizer",IEEE Congress on Evolutionary Computation, pp. 3206 – 3213, 2015.

B. Y. Qu, **J. J. Liang**, Z. Y. Wang and D. M. Liu, “Solving CEC 2015 Multi-modal Competition Problems Using Neighborhood Based Speciation Differential Evolution”, IEEE Congress on Evolutionary Computation, pp. 3214-3219, 2015.

**J. J. Liang**, H. Song, B. Y. Qu, W. Liu & A. K. Qin, “Neural Network Based on Dynamic Multi-Swarm Particle Swarm Optimizer for Ultra-Short-Term Load Forecasting,” the Fifth International Conference on Swarm Intelligence(ICSI 2014), Advances in Swarm Intelligence, 384-391, 2014 ISSN:0302-9743

B. Y. Qu, **J. J. Lian**g, J. M. Xiao, and Z. G. Shang, “Memetic Differential Evolution Based on Fitness Euclidean-Distance Ratio”, IEEE Congress on Evolutionary Computation 2014, pp. 2266-2273, 2014.

**J. J. Liang**, B. Zheng, B. Y. Qu, and H. Song, “Multi-objective Differential Evolution Algorithm Based on Fast Sorting and a Novel Constraints Handling Technique”, IEEE Congress on Evolutionary Computation 2014, pp. 445-450, 2014.