郑州大学计算智能实验室

Computational Intelligence Laboratory

Journal Article

The papers here are for faster dissemination and academic research convenience purposes only, and the copyright of the final papers belongs to the corresponding publishers!

‖ 2024

  • K. J. Qiao, J. Liang*, W. F. Guo*, Z. Hu, K. J. Yu, P. N. Suganthan. Knowledge

    -Embedded Constrained Multiobjective Evolutionary Algorithm Based on

    Structural Network Control Principles for Personalized Drug Targets

    Recognition in Cancer[J]. Information Sciences, 2024: 121033. IF: 8.1. (paper)

‖ 2023

  • J. Liang, Y. Y. Zhang, K. Chen*, B. Y. QU, K. J. Yu, C. T. Yue, P. N. Suganthan. An evolutionary multi-objective method based on dominance and decomposition for feature selection in classification[J].  Science China Information Sciences, 2023, doi: 10.1007/s11432-023-3864-6. IF: 8.8. (paper)

  • S. Y. Zhang, T. L. Yang, J. Liang and C. T. Yue,  A Novel Adaptive Bandit-Based Selection Hyper-Heuristic for Multiobjective Optimization. IEEE Transactions on Systems, Man, and Cybernetics: Systems, doi: 10.1109/TSMC.2023.3299982. IF: 8.7.(paper)

  • J. Liang, Z. Hu, Z. W. Li, K. J. Qiao, and W. F. Guo, Multi-Objective Optimization Based Network Control Principles for Identifying Personalized Drug Targets With Cancer[J]. IEEE Transactions on Evolutionary Computation, doi: 10.1109/TEVC.2023.3303958. IF: 16.497.(paper)

  • Y. X. Li, J Liang, C. T. Yue, K. J. Yu, H Guo. An incremental random walk algorithm for sampling continuous fitness landscapes[J]. Neurocomputing, 2023: 126549. IF: 5.779.  (paper)

  • J Liang, H Guo, K Chen, K. J. Yu, C. T. Yue, Y. P. Ma. A Survey on Intelligent Optimization Approaches to Boiler Combustion Optimization[J]. CAAI Artificial Intelligence Research, 2023, doi: 10.26599/AIR.2023.91

    50014. (paper)

  • K. J. Yu, D. Z. Zhang, J. Liang*, B. Y. Qu, M. N. Liu, K. Chen, C. T. Yue, L. Wang, A Framework Based on Historical Evolution Learning for Dynamic Multiobjective Optimization[J]. IEEE Transactions on Evolutionary Computation, 2023, doi: 10.1109/TEVC.2023.3290485. IF: 16.497.  (paper)(code)

  • J. Liang, Y. Y. Zhang, B. Y. Qu, K. Chen, K. J. Yu, and C. T. Yue. A Multiform Optimization Framework for Multi-objective Feature Selection in Classification, IEEE Transactions on Evolutionary Computation. 2023. IF: 16.497. (paper)(code)

  • Ying Bi, Jing Liang*, Bing Xue, Mengjie Zhang. A Genetic Programming Approach with Building Block Evolving and Reusing to Image Classification,  IEEE Transactions on Evolutionary Computation, 2023. IF: 16.497. (paper)

  • K. J. Qiao, J. Liang*, K. J. Yu, C. T. Yue, H. Y. Lin, D. Z. Zhang, B. Y. Qu. Evolutionary constrained multiobjective optimization: scalable high-dimensional constraint benchmarks and algorithm[J]. IEEE Transactions on Evolutionary Computation, 2023. Doi: 10.1109/TEVC.2023.3281666. IF: 16.497. (paper)(code)

  • K. J. Qiao, J. Liang*, Z. Y. Liu, K. J. Yu, C. T. Yue, B. Y. Qu. Evolutionary multitasking with global and local auxiliary tasks for constrained multi-objective optimization[J]. IEEE/CAA Journal of Automatica Sinica, 2023. Doi: 10.1109/JAS.2023.123336. IF: 7.847. (paper)(code)

  • J. Liang, K Li, K. J. Yu, C. T. Yue*, Y. X. Li, H. Song. A novel differential evolution algorithm based on local fitness landscape information for optimization problems[J]. IEICE TRANSACTIONS on Information and Systems, 2023, E106-D(5): 601-616. IF: 0.695. (paper)

  • J. Liang, Z. L. Chen, Y. N. Wang, X. X. Ban*, K. J. Qiao, K. J. Yu. A dual-population constrained multi-objective evolutionary algorithm with variable auxiliary population size[J]. Complex & Intelligent Systems, 2023. IF: 6.700. (paper)

  • Y. X. Li, J. Liang*, K. J. Yu, C. T. Yue, Y. J. Zhang. Keenness for characterizing continuous optimization problems and predicting differential evolution algorithm performance[J]. Complex & Intelligent Systems, 2023: 1-16. (paper)

  • P. Wang, B. Xue, J. Liang*, M. J. Zhang. Feature Clustering-Assisted Feature Selection with Differential Evolution[J]. Pattern Recognition, 2023. IF: 8.518. (paper)

  • P. Wang, B. Xue, J. Liang, M. J. Zhang. Feature Selection Using Diversity-Based Multi-objective Binary Differential Evolution[J]. Information Sciences, 2023. IF: 8.233. (paper)

  • Z Wu, M Yu*, J.Liang. Parameter optimization of energy-efficient antenna system using period-based memetic algorithm. Expert Systems with Applications. 2023, 214: 119131. IF: 8.665. (paper)

  • L. Yan, W. L. Qi, A. K. Qin, S. X. Yang, D. W. Gong, B. Y. Qu*, J. J. Liang. Manifold clustering-based prediction for dynamic multiobjective optimization [J]. Swarm and Evolutionary Computation, 2023, 77:101254. IF: 10.267. (paper)(code)

  • L. Yan, W. L. Qi, J. J. Liang, B. Y. Qu*, K. J. Yu, C. T. Yue, X. Z. Chai. Inter-individual correlation and Dimension Based Dual Learning for Dynamic Multi-objective Optimization [J]. IEEE Transactions on Evolutionary Computation, 2023. Doi: 10.1109/TEVC.2023.3235196. IF: 16.497. (paper)(code)

  • K. J. Qiao, J. Liang*, K. J. Yu, M. H. Wang, B. Y. Qu, C. T. Yue, Y. N. Guo. A Self-Adaptive Evolutionary Multi-Task Based Constrained Multi-Objective Evolutionary Algorithm [J]. IEEE Transactions on Emerging Topics in Computational Intelligence, 2023. Doi: 10.1109/TETCI.2023.3236633. IF: 4.851. (paper)(code)

  • H. S. Wang, Y. Zhang, J. Liang*, et al. DAFA-BiLSTM: Deep Autoregression Feature Augmented Bidirectional LSTM network for time series prediction[J]. Neural Networks, 2023, 157: 240-256. IF: 9.657. (paper)

  • J. J. Liang, X. X. Ban, K. J. Yu*, B. Y. Qu, K. J. Qiao, C. T. Yue, K. C, K. C. Tan. A Survey on Evolutionary Constrained Multi-objective Optimization [J]. IEEE Transactions on Evolutionary Computation, 2023, 27(2): 201-221. IF: 11.554. (paper) 【ESI Highly Cited Paper】



‖ 2022

  • Y. N. Guo, G. Y. Chen, M. Jiang, D. W. Gong, J. Liang*. A Knowledge guided Transfer Strategy for Evolutionary Dynamic Multiobjective Optimization [J]. IEEE Transactions on Evolutionary Computation, 2022. Doi: 10.1109/TEVC.2022.3222844.  IF: 16.497.(paper)

  • Y. X. Li, K. J. Yu, J. Liang*, C. T. Yue, K. J. Qiao. A landscape-aware particle swarm optimization for parameter identification of photovoltaic models [J]. Applied Soft Computing, 2022,131: 109793. IF：8.263. (paper)(code)

  • D. Yang, L. Wang, K. J. Yu, J. Liang*. A reinforcement learning-based energy management strategy for fuel cell hybrid vehicle considering real-time velocity prediction [J]. Energy Conversion and Managementpap, 2022, 274: 116453. IF: 11.553. (paper)

  • J. Liang, B. Y. Qu, B. L. Li, K. J. Yu, and C. T. Yue. Locating multiple roots of nonlinear equation systems via multi-strategy optimization algorithm with sequence quadratic program[J]. Science China Information Sciences, 2022, 65(7): 1-3. IF=7.275. (paper)

  • J. Liang, H. Guo, K. Chen, K. J. Yu, C. T. Yue, X. Li. An improved Kalman particle swarm optimization for modeling and optimizing of boiler combustion characteristics[J]. Robotica, 2022: 1-11. IF=2.406. (paper)(code)

  • Y. X. Li, J. Liang*, K. J. Yu, K. Chen, Y. N. Guo, C. T. Yue, L. Y. Zhang. Adaptive Local Landscape Feature Vector for Problem Classification and Algorithm Selection[J]. Applied Soft Computing, 2022， Doi: 10.1016/j.asoc.2022.109751. IF：8.263. (paper)(code)

  • J. J. Liang, Z. W. Li, C. T. Yue, Z. Hu, H. Cheng, Z. X. Liu, W. F. Guo*. Multi-modal Optimization to Identify Personalized Biomarkers for Disease Prediction of Individual Patients with Cancer [J]. Briefings in Bioinformatics, 2022, Doi: 10.1093/bib/bbac254. IF: 13.994. (paper)

  • J. J. Liang, H. Y.  Lin, C. T. Yue*, K. J.  Yu, Y. Guo, and K. J. Qiao, Multiobjective Differential Evolution with Speciation for Constrained Multimodal Multiobjective Optimization [J]. IEEE Transactions on Evolutionary Computation, 2022, Doi: 10.1109/TEVC.2022.3194253. IF: 11.554.(paper)(code)

  • K. J. Yu, D. Z. Zhang, J. J. Liang, K. Chen*, C. T. Yue, K. J. Qiao, L. Wang. A Correlation-Guided Layered Prediction Approach for Evolutionary Dynamic Multiobjective Optimization [J]. IEEE Transactions on Evolutionary Computation, 2022, Doi: 10.1109/TEVC.2022.3193287. IF: 11.554.(paper)(code)

  • 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, 2022. Doi: 10.1109/TEVC.2022.3186667. IF: 11.554. (paper)

  • 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 [J]. IEEE Transactions on Evolutionary Computation, 2022. Doi: 10.1109/TEVC.2022.3175065. IF: 11.554. (paper)(code)(CATF fcuntion code)

  • P. Wang, B. Xue, J. J. Liang*, M. Zhang, Differential Evolution Based Feature Selection: A Niching-based Multi-objective Approach [J]. IEEE Transactions on Evolutionary Computation, 2022. Doi: 10.1109/TEVC.2022.3168052. (paper)

  • 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, 2022, doi: 10.1109/TCYB.2022.3163759. IF: 11.448. (paper)(code) (link)

  • K. J. Qiao, J. J. Liang*, B. Y. Qu, K. J. Yu, C. T. Yue, and H. Song. Differential evolution with level-based learning mechanism [J]. Complex System Modeling and Simulation, 2022, 2 (1): 35-58. (paper)(code)

  • Y. Hu , J. Wang, J. J. Liang*, Y. L. Wang, U. Ashraf , C. T. Yue, K. J. Yu. A two-archive model based evolutionary algorithm for multimodal multi-objective optimization problems[J]. Applied Soft Computing, 2022, 119: 108606. IF: 6.725. (paper)(code)

  • 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 [J]. IEEE Transactions on Evolutionary Computation, 2022. IF: 11.554. (paper)(code)

  • M. Y. Yu, J. J. Liang, Z. Wu, Z. L. Yang. A twofold infill criterion-driven heterogeneous ensemble surrogate-assisted evolutionary algorithm for computationally expensive problems [J]. Knowledge-Based Systems, 2022, 236: 107747. IF: 8.139. (paper)

  • K. J. Qiao, J. J. Liang, K. J. Yu, M. H. Yuan, B. Y. Qu, C. T. Yue. Self-adaptive resources allocation-based differential evolution for constrained evolutionary optimization[J]. Knowledge-Based Systems, 2022, 235: 107653. IF: 8.139 .(paper) (code)


‖ 2021

  • P. Wang, B. Xue, J. J. Liang*, M. J. Zhang. Multiobjective Differential Evolution for Feature Selection in Classification [J]. IEEE Transactions on Cybernetics, 2021. IF:11.448. (paper)

  • J. J. Liang, G. L. Chen, B. Y. Qu, C. T. Yue, K. J. Yu, K. J. Qiao. Niche-based cooperative co-evolutionary ensemble neural network for classification [J]. Applied Soft Computing, 2021, 113: 107951. IF:6.725. (paper)

  • J. J. Liang, X. X. Ban, K. J. Yu*, B. Y. Qu, K. J. Qiao. Differential Evolution with Rankings-Based Fitness Function for Constrained Optimization Problems[J]. Applied Soft Computing, 2021: 108016. IF:6.725. (paper) (code)

  • C. T. Yue, P. N. Suganthan*, J. J. Liang*, B. Y. Qu, K. J. Yu, Y. S. Zhu, and Y. Li. Differential Evolution Using Improved Crowding Distance for Multimodal Multiobjective Optimization[J]. Swarm and Evolutionary Computation, 2021, 62: 100849. IF: 7.717. (paper)(code)

  • W. F. Guo, X. T. Yu, Q. Q. Shi, J. J. Liang *, S. W. Zhang*, and T. Zeng*. Performance Assessment of Sample-Specific Network Control Methods for Bulk and Single Cell Biological Data Analysis[J]. PLoS Computational Biology, 2021, 17(5): 1008962. IF: 4.475. (paper)

  • W. F. Guo, S. W. Zhang*, Y. H. Feng, J. J. Liang, T Zeng*, and L. N. Chen*. Network Controllability-Based Algorithm to Target Personalized Driver Genes for Discovering Combinatorial Drugs of Individual Patients[J]. Nucleic Acids Research, 2021, 49(7): 37. IF: 16.971.(paper)

  • M. Y. Yu, J. J. Liang, K. Zhao, and Z. Wu*. An Arbf Surrogate-Assisted Neighborhood Field Optimizer for Expensive Problems[J]. Swarm and Evolutionary Computation, 2021, 13(28): 100972. IF: 7.717.(paper)

  • Y. Hu, B. Y. Qu, J. Wang, J. J. Liang *, Y. L. Wang, K. J. Yu, Y. X. Li, and K. J. Qiao. Short-Term Load Forecasting Using Multimodal Evolutionary Algorithm and Random Vector Functional Link Network-Based Ensemble Learning[J]. Applied Energy, 2021, 285: 116415. IF: 9.746. (paper)

  • K. J. Yu, J. J. Liang*, B. Y. Qu, Y. Luo, and C. T. Yue. Dynamic Selection Preference-Assisted Constrained Multiobjective Differential Evolution[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021: 1-12. IF: 13.451.(paper)

  • K. J. Yu, J. J. Liang*, B. Y. Qu, and C. T. Yue. Purpose-Directed Two-phase Multiobjective Differential Evolution for Constrained Multiobjective Optimization[J]. Swarm and Evolutionary Computation, 2021, 60: 100799. IF: 7.717. (paper)

  • J. J. Liang*, Y. P. Wei, B. Y. Qu, C. T. Yue, and H. Song. Ensemble Learning Based on Fitness Euclidean-Distance Ratio Differential Evolution for Classification[J]. Natural Computing, 2021, 20: 77-87. IF: 1.69. (paper)

  • X. J. Jia, J. J. Liang, K. Zhao, Z. L. Yang, and M. Y. Yu*. Multi-Parameters Optimization for Electromagnetic Acoustic Transducers Using Surrogate-Assisted Particle Swarm Optimizer[J]. Mechanical Systems and Signal Processing, 2021, 152: 107337. IF: 6.823. (paper)


‖ 2020

  • J. J. Liang, K. J. Qiao, C. T. Yue, K. J. Yu, B. Y. Qu*, R. H. Xu, Z. M. Li, and Y. Hu. A Clustering-Based Differential Evolution Algorithm for Solving Multimodal Multi-Objective Optimization Problems[J]. Swarm and Evolutionary Computation, 2020, 60: 100788. IF: 7.717. (paper)(code)

  • J. J. Liang, G. L. Chen, B. Y. Qu, K. J. Yu*, C. T. Yue, K. J. Qiao, and H. Qian*. Cooperative Co-Evolutionary Comprehensive Learning Particle Swarm Optimizer for Formulation Design of Explosive Simulant[J]. Memetic Computing, 2020, 12 (4): 331-341. IF: 5.9.(paper)

  • J. J. Liang, K. J. Qiao, K. J. Yu*, S. L. Ge, B. Y. Qu, R. H. Xu, and K. Li. Parameters Estimation of Solar Photovoltaic Models via A Self-Adaptive Ensemble-Base Differential Evolution[J]. Solar Energy, 2020, 207: 336-346. IF: 5.742. (paper)(code)

  • 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[J]. Energy Conversion and Management, 2020, 207: 112509. IF: 9.709. (paper)

  • Z. P. Cheng, Z. W. Li*, J. J. Liang, J. K. Si, L. H. Dong, and J. F. Gao. Distributed Coordination Control Strategy for Multiple Residential Solar PV Systems in Distribution Networks[J]. International Journal of Electrical Power & Energy Systems, 2020, 117: 105660. IF: 4.63. (paper)

  • 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[J]. Signal Processing, 2020, 167: 107292-107304. IF: 4.662.(paper)

  • J. J. Liang, S. L. Ge, B. Y. Qu, K. J. Yu*, F. G. Liu, H. T. Yang, P. P. Wei, and Z. M. Li. Classified Perturbation Mutation Based Particle Swarm Optimization Algorithm for Parameters Extraction of Photovoltaic Models[J]. Energy Conversion and Management, 2020, 203: 112138. IF: 9.709. (paper) 【ESI Highly Cited Paper】

  • B. Y. Qu, C. Li, J. J. Liang, L. Yan*, K. J. Yu, and Y. S. Zhu. A Self-Organized Speciation Based Multiobjective Particle Swarm Optimizer for Multimodal Multiobjective Problems[J]. Applied Soft Computing, 2020, 86: 105886. IF: 6.725. (paper)

  • M. Y. Yu, X. Li, and J. J. Liang*. A Dynamic Surrogate-Assisted Evolutionary Algorithm Framework for Expensive Structural Optimization[J]. Structural and Multidisciplinary Optimization, 2020, 61(2): 711-729. IF: 4.542. (paper)

  • B. Qu, C. Li, J. Liang, L. Yan, K. Yu, Y. Zhu. A self-organized speciation based multi-objective particle swarm optimizer for multimodal multi-objective problems[J]. Applied Soft Computing, 2020, 86: 105886. (paper)(code)


‖ 2019

  • Z. P. Cheng, Z. W. Li*, J. J. Liang, J. F. Gao, J. K. Si, and S. H. Li. Distributed Economic Power Dispatch and Bus Voltage Control for Droop-Controlled DC Microgrids[J]. Energies, 2019, 12(7):1400. IF: 2.702.(paper)

  • Z. W. Li, Z. P. Cheng*, J. J. Liang, J. K. Si, L. H. Dong, and S. H. Li. Distributed Event-Triggered Secondary Control for Economic Dispatch and Frequency Restoration Control of Droop-Controlled AC Microgrids[J]. IEEE Transactions on Sustainable Energy. 2019, 11(3): 1938-1950. IF: 7.44.(paper)

  • Y. L. Wang, B. Y. Qu, J. J. Liang*, Y. P. Wei, C. T. Yue, Y. Hu, and H. Song. Two-Stage Decomposition Method Based on Cooperation Coevolution for Feature Selection on High-Dimensional Classification[J]. IEEE Access, 2019,7: 163191-163201. IF: 3.745.(paper)

  • J. J. Liang, H. T. Yang, J. J. Gao, C. T. Yue, S. L. Ge, and B. Y. Qu*. MOPSO-Based CNN for Keyword Selection on Google Ads[J]. IEEE Access, 2019, 7: 125387-125400. IF: 3.745.(paper)

  • W. Z. Zhang, G. Q. Li, W. W. Zhang, J. J. Liang, and G. G. Yen*. A Cluster Based PSO with Leader Updating Mechanism and Ring-Topology for Multimodal Multiobjective Optimization[J]. Swarm and Evolutionary Computation, 2019, 50: 100569. IF: 6.912.(paper)

  • J. J. Liang, P. Wang, L. Guo, B. Y. Qu*, C. T. Yue, K. J. Yu, and Y. C. Wang. Multiobjective Flow Shop Scheduling with Limited Buffers Using Hybrid Self-Adaptive Differential Evolution[J]. Memetic Computing, 2019, 11(4): 407-422. IF: 3.860.(paper)

  • 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[J]. Swarm and Evolutionary Computation, 2019, 48: 62-71. IF: 6.912.(paper)(code)

  • Q. K. Pan, L. Gao*, L. Wang, J. J. Liang, and X. Y. Li. Effective Heuristics and Metaheuristics to Minimize Total Flowtime for The Distributed Permutation Flowshop Problem[J]. Expert Systems with Applications, 2019, 124: 309-324. IF: 5.452.(paper)

  • 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[J]. Applied Energy, 2019, 237: 241-257. IF: 8.848.(paper)(code)

  • 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 Multiobjective Pigeon-Inspired Optimization Algorithm[J]. Science China-Information Sciences, 2019, 62(7): 70206. IF: 3.304.(paper)(code)

  • Z. W. Li*, Z. P. Cheng, Y. L. Xu, Y. F. Wang, J. J. Liang, and J. F. Gao. Hierarchical Control of Parallel Voltage Source Inverters in AC Microgrids[C]// The Journal of Engineering, 2019, 2019(16): 1149-1152. (paper)

  • 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[J]. Swarm and Evolutionary Computation, 2019, 44: 1028-1059. IF: 6.912.(paper)(code)

  • B. Y. Qu, J. J. Liang*, Y. S. Zhu and P. N. Suganthan. Solving Dynamic Economic Emission Dispatch Problem Considering Wind Power by Multi-Objective Differential Evolution with Ensemble of Selection Method[J]. Natural Computing, 2019, 18(4): 695-703. IF:0.860.(paper)

  • Y. S. Zhu, B. H. Qiao, Y. Dong, B. Y. Qu, D. Y. Wu. Multiobjective dynamic economic emission dispatch using evolutionary algorithm based on decomposition[J]. IEEJ Transactions on Electrical & Electronic Engineering, 2019, 14(9).1323-1333. (paper)(code)

  • Z. Li, L. Shi, C. Yue, Z. Shang, B. Qu. Differential evolution based on reinforcement learning with fitness ranking for solving multimodal multiobjective problems[J]. Swarm and Evolutionary Computation, 2019. (paper)


‖ 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[J]. Applied Energy, 2018, 226: 408-422. IF: 8.426.(paper)(code)

  • C. T. Yue, B. Y. Qu, and J. J. Liang. A Multiobjective Particle Swarm Optimizer Using Ring Topology for Solving Multimodal Multiobjective Problems[J]. IEEE Transactions on Evolutionary Computation, 2018, 22(5): 805-817. IF: 8.508.(paper)(code)

  • K. J. Yu, L. While, M. Reynolds, X. Wang, J. J. Liang, L. Zhao*, and Z. L. Wang*. Multiobjective Optimization of Ethylene Cracking Furnace System Using Self-Adaptive Multiobjective Teaching-Learning-Based Optimization[J]. Energy, 2018, 148: 469-481. IF: 5.537.(paper)

  • B. Y. Qu, Y. S. Zhu, Y. C. Jiao, M. Y. Wu, P. N. Suganthan, and J. J. Liang*. A Survey on Multiobjective Evolutionary Algorithms for the Solution of the Environmental/Economic Dispatch Problems[J]. Swarm and Evolutionary Computation, 2018, 38: 1-11. IF: 6.330.(paper)

  • G. Li*, J. Wang*, J. J. Liang, and C. T. Yue. Application of Sliding Nest Window Control Chart in Data Stream Anomaly Detection[J]. Symmetry, 2018, 10(4): 113. IF: 2.143.(paper)

  • G. Li, J. Wang*, J. J. Liang*, and C. T. Yue. The Application of a Double CUSUM Algorithm in Industrial Data Stream Anomaly Detection[J]. Symmetry, 2018, 10(7): 264. IF: 2.143.(paper)


‖ 2017

  • B. Y. Qu, Q. Zhou, J. M. Xiao, J. J. Liang*, and P. N. Suganthan. Large Scale Portfolio Optimization Using Multiobjective Evolutionary Algorithms and Pre-Selection Methods[J]. Mathematical Problems in Engineering, 2017, 2017: 1-14. IF: 1.145.(paper)

  • 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[J]. Energy Conversion and Management, 2017, 150: 742-753. IF:6.377.(paper)(code)

  • C. T. Yue, J. J. Liang*, B. F. Lang, and B. Y. Qu. Two-hidden-layer Extreme Learning Machine Based Wrist Vein Recognition System[J]. Big Data & Information Analytics, 2017, 2(1): 59. IF:1.352.(paper)

  • Lynn, N., & Suganthan, P. N. (2017). Ensemble particle swarm optimizer. Applied Soft Computing, 55, 533-548. (paper)(code)


‖ 2016

  • 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[J]. Information Sciences, 2016, 351: 48-66. IF:4.832.(paper)

  • 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[J]. Neurocomputing, 2016, 175: 826-834. IF:3.317.(paper)

  • B. Y. Qu, J. J. Liang*, Z. Y. Wang, Q. Chen, P. N. Suganthan. Novel Benchmark Functions for Continuous Multimodal Optimization with Comparative Results[J]. Swarm and Evolutionary Computation, 2016, 26: 23-34. IF:3.893.(paper)

  • X. Chu*, B. Niu, J. J. Liang, Q. Lu. An Orthogonal-design Hybrid Particle Swarm Optimizer with Application to Capacitated Facility Location Problem[J]. International Journal of Bio-Inspired Computation, 2016, 8(5): 268-285. IF:1.935.(paper)


‖ 2015

  • L. L. Wu, Q. H. Zhou, T. J. Chen, J. J. Liang, X. Wu. Application of Particle Swarm Optimization Method to Incoherent Scatter Radar Measurement of Ionosphere Parameters[J]. Journal of Geophysical Research: Space Physics, 2015, 120(9): 8096-8110. IF:2.733.(paper)

  • Lynn, N., & Suganthan, P. N. (2015). Heterogeneous comprehensive learning particle swarm optimization with enhanced exploration and exploitation. Swarm and Evolutionary Computation, 24, 11-24. (paper)(code)


‖ 2014

  • J. J. Liang, H. Song, B. Y. Qu*. Comparison of Three Different Curves Used in Path Planning Problems Based on Particle Swarm Optimizer[J]. Mathematical Problems in Engineering, 2014, 2014. IF:0.762.(paper)

  • J. J. Liang, B. Y. Qu, X. B. Mao, B. Niu, D.Y. Wang. Differential Evolution Based on Fitness Euclidean-distance Ratio for Multimodal Optimization[J]. Neurocomputing, 2014, 137: 252-260. IF:2.083.(paper)


‖ 2013

  • Y. Y. Han, J. J. Liang, Q. K. Pan, J. Q. Li. Effective Hybrid Discrete Artificial Bee Colony Algorithms for The Total Flowtime Minimization in The Blocking Flowshop Problem[J]. The International Journal of Advanced Manufacturing Technology, 2013, 67(1-4): 397-414. IF:1.779.(paper)

  • B. Y. Qu, P. N. Suganthan, S. Das. A distance-based locally informed particle swarm model for multimodal optimization[J]. IEEE Transactions on Evolutionary Computation, 2013, 17(3): 387-402. (paper)(code)


‖ 2012

  • B. Y. Qu, P. N. Suganthan, and J. J. Liang. Differential Evolution with Neighborhood Mutation for Multimodal Optimization[J]. IEEE Transactions on Evolutionary Computation, 2012, 16(5): 601-614. IF:4.810.(paper)(code)

  • B. Y. Qu, J. J. Liang, P. N. Suganthan. Niching Particle Swarm Optimization with Local Search for Multi-modal Optimization[J]. Information Sciences, 2012, 197: 131-143. IF:3.643,.(paper)(code)

  • K. Z. Gao, Q. K. Pan, J. Q. Li, Y. T. Wang, J. J. Liang. A Hybrid Harmony Search Algorithm for The No-wait Flow-shop Scheduling Problems[J]. Asia-Pacific Journal of Operational Research, 2012, 29(02): 1250012. IF:0.303.(paper)


‖ 2011

  • J. J. Liang, Q. K. Pan, T. J. Chen, L. Wang. Solving The Blocking Flow Shop Scheduling Problem by A Dynamic Multi-Swarm Particle Swarm Optimizer[J]. The International Journal of Advanced Manufacturing Technology, 2011, 55(5-8): 755-762. IF:1.103.(paper)

  • Q. K. Pan, P. N. Suganthan, J. J. Liang, M. F. Tasgetiren. A Local-best Harmony Search Algorithm with Dynamic Sub-harmony Memoriesfor Lot-streaming Flow Shop Scheduling Problem[J]. Expert Systems with Applications, 2011, 38(4): 3252-3259. IF:2.203.(paper)

  • Zhao, S. Z., & Suganthan, P. N. (2011). Two-lbests based multi-objective particle swarm optimizer. Engineering Optimization, 43(1), 1-17. (paper)(code)

  • B. Y. Qu*, P. N. Suganthan*, "Constrained Multi-Objective Optimization Algorithm with Ensemble of Constraint Handling Methods", Engineering Optimization, vol. 43,no.4,pp.403-416, Mar 2011. (paper)(code)


‖ 2010

  • Q. K. Pan, P. N. Suganthan, M. F. Tasgetiren, J. J. Liang. A Self-Adaptive Global Best Harmony Search Algorithm for Continuous Optimization Problems[J]. Applied Mathematics and Computation, 2010, 216(3): 830-848. IF:1.536.(paper)

  • Q. K. Pan, P. N. Suganthan, J. J. Liang, M. F. Tasgetiren. A Local-best Harmony Search Algorithm with Dynamic Subpopulations[J]. Engineering Optimization, 2010, 42(2): 101-117. IF:0.966.(paper)

  • B. Y. Qu*, P. N. Suganthan, “Multi-Objective Evolutionary Algorithms based on the Summation of Normalized Objectives and Diversified Selection”, Information Sciences, vol. 180, no. 17, pp. 3170-3181, Sept. 2010. (paper)(code)


‖ 2007

  • V. L. Huang, P. N. Suganthan, J. J. Liang, C. C. Chan. Improving the performance of a FBG sensor network using a novel dynamic multi-swarm particle swarm optimizer[J]. Proceedings of SPIE - The International Society for Optical Engineering, 2007, 1(8):373-378.(paper)


‖ 2006

  • J. J. Liang, C. C. Chan, P. N. Suganthan, V. L. Huang. Wavelength Detection in FBG Sensor Network Using Tree Search DMS-PSO[J]. IEEE Photonics Technology Letters, 2006, 18(12): 1305-1307. IF:2.468. (paper)

  • J. J. Liang, P. N. Suganthan, A. K. Qin, S. Baska. Comprehensive Learning Particle Swarm Optimizer for Global Optimization of Multimodal Functions[J]. IEEE Transactions on Evolutionary Computation, 2006, 10(3): 281-295. IF:11.554. (paper)(code)

  • V. L. Huang, P. N. Suganthan, and J. J. Liang*. Comprehensive Learning Particle Swarm Optimizer for Solving Multiobjective Optimization Problems[J]. International Journal of Intelligent Systems, 2006, 21(2): 209-226. IF: 0.429.(paper)

  • J. J. Liang*, S. Baskar, P. N. Suganthan, and A. K. Qin. Performance Evaluation of Multiagent Genetic Algorithm[J]. Natural Computing, 2006, 5(1): 83-96(14). IF: 1.495.(paper)


‖ 2005

  • S. Baskar, A. Alphones, P. N. Suganthan, and J. J. Liang*. Design of Yagi-Uda Antennas Using Comprehensive Learning Particle Swarm Optimisation[J]. IEEE Proceedings on Microwaves, Antenna and Propagation, 2005, 152(5): 340-346. IF: 0.494.(paper)




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