郑州大学计算智能实验室

Computational Intelligence Laboratory

Conference Paper


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

‖ 2023

  • K. J. Qiao, J. J. Liang, Y. Bi, K. J. Yu, C. T. Yue, B. Y. Qu. An Unconstrained

    Auxiliary Framework for Constrained Many-Objective Optimization[C]//2023

    5th International Conference on Data-driven Optimization of Complex

    Systems (DOCS). IEEE, 2023: 1-8. (paper)

  • J. Liang, X. D. Sui, C. T. Yue, M. Y. Yu. Differential Evolution Using 

    Interpolation Strategy for Multimodal Multiobjective Optimization[C]//2023

    3rd International Symposium on Computer Technology and Information Science

    (ISCTIS), 2023: 764-769.(paper)

  • L. Y. Zhu, F. F. Zhang, X. D. Zhu, K Chen*, M. J. Zhang. Sample-Aware

    Surrogate-Assisted Genetic Programming for Scheduling Heuristics Learning

    in Dynamic Flexible Job Shop Scheduling[C]//Proceedings of the Genetic

    and Evolutionary Computation Conference, pp. 384-392, 2023.(paper)

‖ 2022

  • J. Liang, J. T. Yang, C. T. Yue, G.P Li, K. J. Yu and B. Y. Qu. A Multimodal Multiobjective Genetic Algorithm for Feature Selection[C]//2022 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2022

‖ 2021

  • K. J. Qiao, J. J. Liang*, K. J. Yu, B. Y. Qu, C. T. Yue, and G. P. Li. A Self-Adaptive Multi-Task Differential Evolution Algorithm[C]// Asian Conference on Artificial Intelligence Technology, 2021.

  • J. J. Liang, H. Guo, K. J. Yu, B. Y. Qu, C. T. Yue, and K. J. Qiao*. An Improved Composite Differential Evolution with Self-Adaptive Mutation Strategy for Identifying Photovoltaic Model Parameters[C]// Asian Conference on Artificial Intelligence Technology, 2021.

  • J. J. Liang, L. Y. Zhang, K. J. Yu, B. Y. Qu, C. T. Yue, and K. J. Qiao*. A Differential Evolution Based Self-Adaptive Multi-Task Evolutionary Algorithm[C]// Asian Conference on Artificial Intelligence Technology, 2021.

  • X. X. Ban, J. J. Liang*, K. J. Yu, K. J. Qiao, K. Li and Z. L. Chen. A Two-Stage Algorithm for Solving Constrained Multi-Objective Optimization Problems[C]// China Automation Congress, 2021.

  • Y. Hu, J. J. Liang*, B. Y. Qu, J. Wang, Y. L. Wang, and P. P. Wei. Evolutionary Ensemble Learning Using Multimodal Multi-Objective Optimization Algorithm Based on Grid for Wind Speed Forecasting [C]// 2021 IEEE Congress on Evolutionary Computation, pp. 1727-1734, 2021.(paper)


‖ 2020

  • K. J. Qiao, J. J. Liang, K. J. Yu, B. Y. Qu, C. T. Yue, and R. H. Xu. Parameter Extraction of the Photovoltaic Model via an Improved Composite Differential Evolution[C]// China Automation Congress, pp. 4868-4873, 2020.(paper)

  • J. J. Liang, P. S. Li, H. Zhao*, L. Han, and M. L. Qu. Forest Species Classification of UAV Hyperspectral Image Using Deep Learning[C]// China Automation Congress, pp. 7126-7130, 2020.(paper)

  • 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[C]// IEEE Congress on Evolutionary Computation, pp. 1-8, 2020.(paper)


‖ 2019

  • J. Wang, C. H. Zhao, J. J. Liang*, C. T. Yue, X. Y. Ren, and K. Ba. Chromosome Medial Axis Extraction Method Based on Graphic Geometry and Competitive Extreme Learning Machines Teams (CELMT) Classifier for Chromosome Classification[C]// International Conference on Bio-Inspired Computing: Theories and Applications, pp. 550-564, 2019.(paper)

  • J. J. Liang, P. P. Wei*, B. Y. Qu, K. J. Yu, C. T. Yue, Y. Hu, and S. L. Ge. Ensemble Learning Based on Multimodal Multiobjective Optimization[C]// International Conference on Bio-Inspired Computing: Theories and Applications, pp. 299-313, 2019.(paper)

  • J. Wang, B. Wang, J. J. Liang*, K. J. Yu, C. T. Yue, and X. Y. Ren. Ensemble Learning via Multimodal Multiobjective Differential Evolution and Feature Selection[C]// International Conference on Bio-Inspired Computing: Theories and Applications, pp. 439-453, 2019.(paper)

  • J. J. Liang, Z. M. Li*, B. Y. Qu, K. J. Yu, K. J. Qiao, and S. L. Ge. A Knee Point based NSGA-II Multi-Objective Evolutionary Algorithm[C]// International Conference on Bio-Inspired Computing: Theories and Applications, pp. 454-467, 2019.(paper)

  • J. J. Liang, Y. X. Li, B. Y. Qu, K. J. Yu, and Y Hu. Mutation Strategy Selection Based on Fitness Landscape Analysis: A Preliminary Study[C]// International Conference on Bio-Inspired Computing: Theories and Applications, pp. 284-298, 2019.(paper)

  • U. Ashraf, J. J. Liang, A. Akhtar, K. J. Yu, Y. Hu, C. T. Yue, A. M. Masood and M. Kashif. Meta-Heuristic Hybrid Algorithmic Approach for Solving Combinatorial Optimization Problem(TSP) [C]// International Conference on Bio-Inspired Computing: Theories and Applications, pp. 622-633, 2019.(paper)

  • H. Song, A. K. Qin, P. W. Tsai, and J. J. Liang. Multitasking Multi-Swarm Optimization[C]// IEEE Congress on Evolutionary Computation, pp. 1937-1944, 2019.(paper)

  • K. J. Yu, S. L. Ge, B. Y. Qu, and J. J. Liang. A Modified Particle Swarm Optimization for Parameters Identification of Photovoltaic Models[C]// IEEE Congress on Evolutionary Computation, pp.2634-2641, 2019.(paper)

  • S. Cheng, H. Lu, Y. N. Guo, X. J. Lei, J. J. Liang, J. F. Chen, and Y. H. Shi. Dynamic Multimodal Optimization: A Preliminary Study[C]// IEEE Congress on Evolutionary Computation, pp. 279-285, 2019.(paper)

  • J. J. Liang, H. T. Yang, W. T. Sun, and J. J. Gao. PSO-Based CNN for Keyword Selection on Google Ads[C]// IEEE Congress on Evolutionary Computation, pp. 562-569, 2019.(paper)

  • C. T. Yue, J. J. Liang*, B. Y. Qu, K. J. Yu, and H. Song. Multimodal Multiobjective Optimization in Feature Selection[C]// IEEE Congress on Evolutionary Computation, pp. 302-309, 2019.(paper)


‖ 2018

  • J. J. Liang, P. Wang, C. T. Yue, K. J. Yu, Z. H. Li, and B. Y. Qu. Multi-Objective Brainstorm Optimization Algorithm for Sparse Optimization[C]// IEEE Congress on Evolutionary Computation, pp. 1-8, 2018.(paper)

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

  • 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[C]// International Conference on Swarm Intelligence, pp. 550-560, 2018.(paper)(code)


‖ 2017

  • 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[C]// International Conference on Extreme Learning Machines, pp. 12-21, 2017.(paper)

  • M. Y. Yu*, J. J. Liang, B. Y. Qu, and C. T. Yue. Optimization of UWB Antenna Based on Particle Swarm Optimization Algorithm[C]// International Symposium on Intelligence Computation and Applications, pp. 86-97, 2017.(paper)

  • J. J. Liang, M. Y. Yu, C. T. Yue, M. M. Li, and Z. X. Yue. Routing Algorithm Based on SPSO[C]// Electronic and Automation Control Conference, pp. 1350-1354, 2017.(paper)

  • B. L. Li, J. J. Liang*, C. T. Yue, and B. Y. Qu. Multivariant Optimization Algorithm with Bimodal-gauss[C]// International Conference on Simulated Evolution and Learning, pp. 920-928, 2017.(paper)

  • 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[C]// International Conference on Simulated Evolution and Learning, pp. 911-919, 2017.(paper)


‖ 2016

  • J. J. Liang, C. T. Yue, and B. Y. Qu. Multimodal Multi-Objective Optimization: A preliminary study[C]// IEEE Congress on Evolutionary Computation, pp. 2454-2461, 2016.(paper)

  • Y. Jiao, L. Yang, B. Y. Qu*, D. Liu, J. J. Liang, and J. Xiao. Novel Local Particle Swarm Optimizer for Multimodal Optimization[C]// International Conference in Swarm Intelligence, pp. 571-578, 2016.(paper)


‖ 2015

  • L. L. Wu*, J. J. Liang, T. J. Chen, Y. Q. Wang, and O. D. Crisalle. DMS-PSO Based Tuning of PI Controllers for Frequency Control of a Hybrid Energy System[C]// International Conference in Swarm Intelligence, pp. 208-215, 2015.(paper)

  • J. J. Liang, L. Guo, R. Liu, and B.Y. Qu. A Self-Adaptive Dynamic Particle Swarm Optimizer[C]// IEEE Congress on Evolutionary Computation, pp. 3206 -3213, 2015.(paper)

  • 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[C]// IEEE Congress on Evolutionary Computation, pp. 3214-3219, 2015.(paper)


‖ 2014

  • J. J. Liang, H. Song, B. Y. Qu, W. Liu, and A. K. Qin. Neural Network Based on Dynamic Multi-Swarm Particle Swarm Optimizer for Ultra-Short-Term Load Forecasting[C]// International Conference on Swarm Intelligence, pp. 384-391, 2014.(paper)

  • B. Niu, H. Huang, B. Ye, L. Tan, and J. J. Liang. Fully Learned Multi-swarm Particle Swarm Optimization[C]// International Conference on Swarm Intelligence, pp. 150-157, 2014.(paper)

  • W. Liu, H. Song, J. J. Liang, B.Y. Qu, and A.K. Qin. Neural Network Based on Self-Adaptive Differential Evolution for Ultra-Short-Term Power Load Forecasting[C]// International Conference on Intelligent Computing, pp. 403-412, 2014.(paper)

  • B. Zheng, B. Y. Qu, J. J. Liang, and H. Song. Multi-Objective Comprehensive Learning Particle Swarm Optimization based on Summation of Normalized Objectives and Diversified Selection[C]// Chinese Control and Decision Conference, pp. 1339-1343, 2014.(paper)

  • B. Y. Qu, J. J. Liang, J. M. Xiao, and Z. G. Shang. Memetic Differential Evolution Based on Fitness Euclidean-Distance Ratio[C]// IEEE Congress on Evolutionary Computation, pp. 2266-2273, 2014.(paper)

  • 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[C]// IEEE Congress on Evolutionary Computation, pp. 445-450, 2014.(paper)

  • Z. H. Li, Z. G. Shang, J. J. Liang, and B. Y. Qu. Differential Evolution Strategy based on the Constraint of Fitness Values Classification[C]// IEEE Congress on Evolutionary Computation, pp. 1454-1460, 2014.(paper)

  • Z. H. Li, Z. G. Shang, J. J. Liang, and B. Y. Qu. Feature Selection based on Manifold-Learning with Dynamic Constraint-Handling Differential Evolution[C]// IEEE Congress on Evolutionary Computation, pp. 332-337, 2014.(paper)


‖ 2013

  • B. Niu, Q. Q. Duan, and J. J. Liang. Adaptive Bacterial Foraging Algorithm for Data Clustering[C]// International Conference on Intelligent Data Engineering and Automated Learning, pp. 577-584, 2013.

  • Min Niu, X. B. Mao, J. J. Liang, and Ben Niu. Object Tracking Based on Extended SUR Fand Particle Filter[C]// International Conference on Intelligent Computing, pp. 649–657, 2013.(paper)

  • C. Chen, J. J. Liang, B. Y. Qu, and B. Niu. Using Dynamic Multi-Swarm Particle Swarm Optimizer to Improve the Image Sparse Decomposition Based on Matching Pursuit[C]// International Conference on Intelligent Computing, pp. 587–595, 2013.(paper)

  • T. J. Chen, L.L. Wu, J. J. Liang, and Q. H. Zhou. Research and Analysis on Ionospheric Composition Based on Particle Swarm Optimization[C]//Intelligent Computing Theories and Technology, pp. 596-604, 2013.(paper)

  • B. Niu, H. L. Huang, L. J. Tan, and J. J. Liang. Multi-swarm Particle Swarm Optimization with a Center Learning Strategy[C]// International Conference on Swarm Intelligence, pp. 72–78, 2013.(paper)

  • J. J. Liang and B.Y. Qu. Large-scale Portfolio Optimization Using Multi-objective Dynamic Mutli-Swarm Particle Swarm Optimizer[C]// IEEE Symposium on Swarm Intelligence, pp. 1-6, 2013.(paper)

  • J. J. Liang, H. Song, and B.Y. Qu. Performance Evaluation of Dynamic Multi-Swarm Particle Swarm Optimizer with Different Constraint Handling Methods on Path Planning Problems[C]// IEEE Symposium Series on Computational Intelligence, pp. 65-71, 2013.(paper)


‖ 2012

  • 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 [C]// International Conference on Intelligent Computing, pp. 252-260, 2012.(paper)

  • J. J. Liang, H. Song, B. Y. Qu, and X. B. Mao. Path Planning Based on Dynamic Multi-Swarm Particle Swarm Optimizer with Crossover[C]// Intelligent Computing Theories and Applications, pp. 159-166, 2012.(paper)

  • J. J. Liang, W. X. Zhang, B. Y. Qu, and T. J. Chen. Multiobjective Dynamic Multi-Swarm Particle Swarm Optimization for Environmental/Economic Dispatch Problem[C]// Intelligent Computing Technology, pp. 657-664, 2012.(paper)

  • Z. G. Shang, Z. H. Li, and J. J. Liang. Real Coded Feature Selection Integrated with Self-Adaptive Differential Evolution Algorithm[C]// Emerging Intelligent Computing Technology and Applications, pp. 481-488, 2012.(paper)

  • B. Y. Qu, J. J. Liang, P. N. Suganthan, and T. J. Chen. Ensemble of Clearing Differential Evolution for Multi-modal Optimization[C]// International Conference on Swarm Intelligence, pp. 350-357, 2012.(paper)

  • J. J. Liang, B. Y. Qu, P. N. Suganthan, and B. Niu. Dynamic Multi-Swarm Particle Swarm Optimization for Multi-Objective Optimization Problems[C]// IEEE Congress on Evolutionary Computation, pp. 605-612, 2012.(paper)

  • J. J. Liang, S. T. Ma, B. Y. Qu, and B. Niu. Strategy Adaptative Memetic Crowding Differential Evolution for Multimodal Optimization[C]// IEEE Congress on Evolutionary Computation, pp. 2885-2891, 2012.(paper)

  • J. J. Liang, X. B, Mao, B. Y Qu, B. Niu*, and T. J. Chen. Elite Multi-Group Differential Evolution[C]// IEEE Congress on Evolutionary Computation, pp. 1775-1781, 2012.(paper)

  • Z. G. Shang, Z. H. Li, J. J. Liang, and B. Niu. Control Parameters Self-Adaptation in Differential Evolution Based on Intrisic Structure Information[C]// IEEE Congress on Evolutionary Computation, pp. 349-354, 2012.(paper)

  • Z. H. Li, Z. G. Shang, J. J. Liang, and B. Niu. An Improved Differential Evolution for Constrained Optimization with Dynamic Constraint-Handling Mechanism[C]// IEEE World Congress on Computational Intelligence, pp. 343-348, 2012.(paper)


‖ 2011

  • J. J. Liang, B. Y. Qu，and S. T Ma. Memetic Fitness Euclidean-Distance Particle Swarm Optimization for Multi-modal Optimization[C]// International Conference on Intelligent Computing, pp. 378-385, 2011.(paper)

  • Liang, J. J. , &  Suganthan, P. N. . (2011). Dynamic multi-swarm particle swarm optimizer with harmony search[C]// IEEE Congress on Evolutionary Computation. IEEE.(paper)(code)


‖ 2010

  • J. J. Liang, Q. K. Pan, and T.J. Chen. A Dynamic Multi-Swarm Particle Swarm Optimizer for Blocking Flow Shop Scheduling[C]// International Conference on Bio-Inspired Computing: Theory and Applications, pp. 323-327, 2010.(paper)

  • J. J. Liang, Z. G. Shang, and Z. H. Li. Coevolutionary Comprehensive Learning Particle Swarm Optimizer[C]// IEEE Congress on Evolutionary Computation, pp. 1505-1512, 2010.(paper)

  • Y. Y Han, Q. K. Pan, J. J. Liang, and J. Q. Li. A Hybrid Discrete Harmony Search Algorithm For Blocking Flow Shop Scheduling[C]// International Conference on Bio-Inspired Computing: Theory and Applications, pp. 435-438, 2010.(paper)

  • W. J. Ren, Q. K. Pan, and J. J. Liang*. An Improved Harmony Search Algorithm for Multi-Dimensional Function Optimization Problem[C]// Bio-Inspired Computing: Theory and Applications, pp. 391-395, 2010.(paper)

  • W. J. Ren, Q. K. Pan, J. Q. Li, and J. J. Liang*. Tabu Search Algorithm for Solving No-idle Permutation Flow Shop Scheduling Problem[C]// Bio-Inspired Computing: Theory and Applications, pp. 449 – 453, 2010.(paper)

  • Z. H. Li, J. J. Liang, X. He, and Z. G. Shang. Differential Evolution with Dynamic Constraint-Handling Mechanism[C]// IEEE Congress on Evolutionary Computation, pp. 1899-1906, 2010.(paper)

  • J. H. Zhang, Z. G. Shang, J. J. Liang, L. Wang, and J. Yun. Analyzing Conformation of Fusion Protein on Bivalent Single-Chain Antibody with (Gly4Ser)n[C]// International Conference on Bioinformatics and Biomedical Engineering, pp. 1-4, 2010.(paper)

  • Q. K. Pan*, J. H. Duan, J. J. Liang, K. Z. Gao, and J. Q. Li. A Novel Discrete Harmony Search Algorithm for Scheduling Lot-Streaming Flow Shops[C]// Chinese Control and Decision Conference, pp. 1531-1536, 2010.(paper)

  • K. Z. Gao, H. Li, Q. K. Pan, J. Q. Li, and J. J. Liang. Hybrid Heuristics Based on Harmony Search to Minimize Total Flow Time in No-Wait Flow Shop[C]// Chinese Control and Decision Conference, pp. 1184-1188, 2010.(paper)

  • J. Q. Li*, Q. K. Pan, S. X. Xie, J. J. Liang, L. P. Zheng, and K. Z. Gao. A Hybrid Particle Swarm Optimization Algorithm for Bi-Criteria Flexible Job-Shop Scheduling Problem[C]// Chinese Control and Decision Conference, pp. 1537-1541, 2010.(paper)

  • J. Q. Li, Q. K. Pan, S. X. Xie, and J. J. Liang. A Hybrid Pareto-Based Tabu Search for Multi-Objective Flexible Job Shop Scheduling Problem with E/T Penalty[C]// Advances in Swarm Intelligence - First International Conference, pp. 620-627, 2010.(paper)


‖ 2009

  • F. R. Wang, W. H. Wang, Q. K. Pan, F. C. Zuo, and J. J. Liang. A Novel Online Test-Sheet Composition Approach for Web-Based Testing[C]// IEEE International Symposium on IT in Medicine & Education, pp. 700-705, 2009.(paper)

  • L. P. Zheng*, Q. K. Pan, G. Y. Li, and J. J. Liang. Improvement of Grayscale Image Segmentation Based on PSO Algorithm[C]// Fourth International Conference on Computer Sciences and Convergence Information Technology, pp. 442-446, 2009.(paper)

  • L. P. Zheng, G. Y. Li, J. J. Liang, and Q. K. Pan. Improved 2D Maximum Entropy Threshold Segmentation Method Based on PSO[C]// International Joint Conference on Computational Intelligence, pp. 287-291, 2009.(paper)


‖ 2008

  • S. Z. Zhao, J. J. Liang, P. N. Suganthan, and M. F. Tasgetiren. Dynamic Multi-Swarm Particle Swarm Optimizer with Local Search for Large Scale Global Optimization[C]// Proceedings of IEEE Congress on Evolutionary Computation, pp. 3845-3852, 2008.(paper)(code)


‖ 2006

  • J. J. Liang and P. N. Suganthan. Dynamic Multi-Swarm Particle Swarm Optimizer with a Novel Constraint-Handling Mechanism[C]// IEEE Congress on Evolutionary Computation, pp. 9-16, 2006.(paper)(code)

  • J. J. Liang and P. N. Suganthan. Adaptive Comprehensive Learning Particle Swarm Optimizer with History Learning[C]// International Conference on Simulated Evolution and Learning, pp. 213-220, 2006.(paper)


‖ 2005

  • J. J. Liang, C. C. Chan, V. L. Huang, and P. N. Suganthan. Improving the Performance of a FBG Sensor Network Using a Novel Dynamic Multi-Swarm Particle Swarm Optimizer[C]// Proceedings of SPIE Symposium on Optics East, pp. 191-197, 2005.(paper)

  • J. J. Liang and P. N. Suganthan. Dynamic Multi-Swarm Particle Swarm Optimizer with Local Search[C]// Proceedings of IEEE Congress on Evolutionary Computation, pp. 522-528, 2005.(paper)

  • J. J. Liang and P. N. Suganthan. Dynamic Multi-Swarm Particle Swarm Optimizer[C]// Proceedings of IEEE International Swarm Intelligence Symposium, pp. 124-129, 2005.(paper)

  • J. J. Liang, P. N. Suganthan, and K. Deb. Novel Composition Test Functions for Numerical Global Optimization[C]// Proceedings of IEEE International Swarm Intelligence Symposium, pp. 68-75, 2005.(paper)


‖ 2004

  • J. J. Liang, A. K. Qin, P. N. Suganthan, and S. Baskar. Particle Swarm Optimization Algorithms with Novel Learning Strategies[C]// International Conference on Systems, Man and Cybernetics, pp. 3659 - 3664, 2004.(paper)

  • J. J. Liang, A. K. Qin, P. N. Suganthan, and S. Baskar. Evaluation of Comprehensive Learning Particle Swarm Optimizer[C]// International Conference on Neural Information Processing, pp. 230-235, 2004.(paper)

  • K. Qin, P. N. Suganthan, and J. J. Liang. A New Generalized LVQ Algorithm Via Harmonic to Minimum Distance Measure Transition[C]// IEEE International Conference on Systems, Man and Cybernetics, pp. 4821 - 4825, 2004.(paper)




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