工程科学学报 Chinese Journal of Engineering 多目标粒子群优化算法研究综述 冯茜李擎全威裴轩墨 Overview of multiobjective particle swarm optimization algorithm FENG Qian.LI Qing.QUAN Wei.PEI Xuan-mo 引用本文： 冯茜，李擎，全威，裴轩墨.多目标粒子群优化算法研究综述[J].工程科学学报，2021,43(6)：745-753.doi: 10.13374j.issn2095-9389.2020.10.31.001 FENG Qian,LI Qing,QUAN Wei,PEI Xuan-mo.Overview of multiobjective particle swarm optimization algorithm[J].Chinese Journal of Engineering,.2021,436:745-753.doi:10.13374f.issn2095-9389.2020.10.31.001 在线阅读View online::htps:/doi.org/10.13374.issn2095-9389.2020.10.31.001 您可能感兴趣的其他文章 Articles you may be interested in 基于自适应搜索的免疫粒子群算法 Immune particle swarm optimization algorithm based on the adaptive search strategy 工程科学学报.2017,391)：125 https::/doi.org10.13374.issn2095-9389.2017.01.016 基于粒子群算法的转炉用氧节能优化调度 Optimal scheduling of converter oxygen based on particle swarm optimization 工程科学学报.2021,43(2：279htps:doi.org/10.13374.issn2095-9389.2020.04.02.002 分布式一致性最优化的梯度算法与收敛分析 Distributed gradient-based consensus optimization algorithm and convergence analysis 工程科学学报.2020,42(4：434 https::/1doi.org/10.13374j.issn2095-9389.2019.09.05.005 确定性多变量自校正控制的稳定性、收敛性和鲁棒性 Stability,convergence,and robustness of deterministic multivariable self-tuning control 工程科学学报.2019,41(9%：1215 https:1oi.org10.13374.issn2095-9389.2019.09.014 一种改进的人工蜂群算法—粒子蜂群算法 An improved artificial bee colony algorithm:particle bee colony 工程科学学报.2018.40(7)：871 https:/doi.org10.13374.issn2095-9389.2018.07.014 固溶时效工艺对6016铝合金力学性能的影响及多目标优化 Effect of solution and aging processes on the mechanical properties of 6016 aluminum alloy and multi-objective optimization 工程科学学报.2017,39(1：75htps/doi.org/10.13374issn2095-9389.2017.01.010多目标粒子群优化算法研究综述 冯茜 李擎 全威 裴轩墨 Overview of multiobjective particle swarm optimization algorithm FENG Qian, LI Qing, QUAN Wei, PEI Xuan-mo 引用本文: 冯茜, 李擎, 全威, 裴轩墨. 多目标粒子群优化算法研究综述[J]. 工程科学学报, 2021, 43(6): 745-753. doi: 10.13374/j.issn2095-9389.2020.10.31.001 FENG Qian, LI Qing, QUAN Wei, PEI Xuan-mo. Overview of multiobjective particle swarm optimization algorithm[J]. Chinese Journal of Engineering, 2021, 43(6): 745-753. doi: 10.13374/j.issn2095-9389.2020.10.31.001 在线阅读 View online: https://doi.org/10.13374/j.issn2095-9389.2020.10.31.001 您可能感兴趣的其他文章 Articles you may be interested in 基于自适应搜索的免疫粒子群算法 Immune particle swarm optimization algorithm based on the adaptive search strategy 工程科学学报. 2017, 39(1): 125 https://doi.org/10.13374/j.issn2095-9389.2017.01.016 基于粒子群算法的转炉用氧节能优化调度 Optimal scheduling of converter oxygen based on particle swarm optimization 工程科学学报. 2021, 43(2): 279 https://doi.org/10.13374/j.issn2095-9389.2020.04.02.002 分布式一致性最优化的梯度算法与收敛分析 Distributed gradient-based consensus optimization algorithm and convergence analysis 工程科学学报. 2020, 42(4): 434 https://doi.org/10.13374/j.issn2095-9389.2019.09.05.005 确定性多变量自校正控制的稳定性、收敛性和鲁棒性 Stability, convergence, and robustness of deterministic multivariable self-tuning control 工程科学学报. 2019, 41(9): 1215 https://doi.org/10.13374/j.issn2095-9389.2019.09.014 一种改进的人工蜂群算法——粒子蜂群算法 An improved artificial bee colony algorithm: particle bee colony 工程科学学报. 2018, 40(7): 871 https://doi.org/10.13374/j.issn2095-9389.2018.07.014 固溶时效工艺对6016铝合金力学性能的影响及多目标优化 Effect of solution and aging processes on the mechanical properties of 6016 aluminum alloy and multi-objective optimization 工程科学学报. 2017, 39(1): 75 https://doi.org/10.13374/j.issn2095-9389.2017.01.010