郑州大学计算智能实验室

Computational Intelligence Laboratory

Code

本栏提供两种方式下载:

1) 百度网盘(提取码为‘1234’);

2) GitHub;


  • 1) MMODE_ICD.zip

    2) MMODE_ICD.zip

    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,中科院一区.

  • 1) code_MMODE_CSCD.zip

    2) code_MMODE_CSCD.zip

    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, 中科院一区.

  • 1) SEDE.zip

    2) SEDE.zip

    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, 中科院二区.

  • 1) SSMOPSO code.zip

    2) SSMOPSO code.zip

    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.

  • 1) MMO.zip

    2) MMO.zip

    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, 中科院二区.

  • 1) PGJAYA.zip

    2) PGJAYA.zip

    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, 中科院一区.

  • 1) Codes of MMODE.zip

    2) Codes of MMODE.zip

    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, 中科院二区.

  • 1) code.zip

    2) code.zip

    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.

  • 1) MLBSA code.rar

    2) MLBSA code.rar

    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,中科院一区.

  • 1) MO_Ring_PSO_SCD_codes.zip

    2) MO_Ring_PSO_SCD_codes.zip

    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, 中科院一区.

  • 1) IJAYA code.rar

    2) IJAYA code.rar

    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, 中科院一区.

  • 1) 2017-ASOC-EPSO.zip

    2) 2017-ASOC-EPSO.zip

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

  • 1) 2015-SWEVO-HCLPSO.zip

    2) 2015-SWEVO-HCLPSO.zip

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

  • 1) 2013-TEC-LIPS.rar

    2) 2013-TEC-LIPS.rar

    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.

  • 1) 2012-TEC-DE-niching.zip

    2) 2012-TEC-DE-niching.zip

    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, 中科院一区.

  • 1) 2012-INS-Niching.rar

    2) 2012-INS-Niching.rar

    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, 中科院二区.

  • 1) 2011-Eng-Opt-2LB-MOPSO.zip

    2) 2011-Eng-Opt-2LB-MOPSO.zip

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

  • 1) 2011-Eng-Opt-Ens-Const-MODE

    2) 2011-Eng-Opt-Ens-Const-MODE

    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.

  • 1) 2010-Inf-Sci-Fast-Sort-MODE.rar

    2) 2010-Inf-Sci-Fast-Sort-MODE.rar

    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.

  • 1) 2006-IEEE-TEC-CLPSO.rar

    2) 2006-IEEE-TEC-CLPSO.rar

    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, 中科院一区.