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融合张角拥挤控制策略的高维多目标优化

陈振兴 严宣辉 吴坤安 白猛

陈振兴, 严宣辉, 吴坤安, 白猛. 融合张角拥挤控制策略的高维多目标优化. 自动化学报, 2015, 41(6): 1145-1158. doi: 10.16383/j.aas.2015.c140555
引用本文: 陈振兴, 严宣辉, 吴坤安, 白猛. 融合张角拥挤控制策略的高维多目标优化. 自动化学报, 2015, 41(6): 1145-1158. doi: 10.16383/j.aas.2015.c140555
CHEN Zhen-Xing, YAN Xuan-Hui, WU Kun-An, BAI Meng. Many-objective Optimization Integrating Open Angle Based Congestion Control Strategy. ACTA AUTOMATICA SINICA, 2015, 41(6): 1145-1158. doi: 10.16383/j.aas.2015.c140555
Citation: CHEN Zhen-Xing, YAN Xuan-Hui, WU Kun-An, BAI Meng. Many-objective Optimization Integrating Open Angle Based Congestion Control Strategy. ACTA AUTOMATICA SINICA, 2015, 41(6): 1145-1158. doi: 10.16383/j.aas.2015.c140555

融合张角拥挤控制策略的高维多目标优化

doi: 10.16383/j.aas.2015.c140555
基金项目: 

国家自然科学基金(61175123)资助

详细信息
    作者简介:

    陈振兴 福建师范大学数学与计算机科学学院硕士研究生. 主要研究方向为计算智能与数据挖掘.E-mail: czx_ky@yeah.net

    通讯作者:

    严宣辉 福建师范大学数学与计算机科学学院副教授. 主要研究方向为人工智能与数据挖掘. E-mail: yan@fjnu.edu.cn

Many-objective Optimization Integrating Open Angle Based Congestion Control Strategy

Funds: 

Supported by National Natural Science Foundation of China (61175123)

  • 摘要: 对于高维多目标优化问题,随着目标维数的增加,种群中非被支配解的比例剧增, 严重降低了种群的进化压力.为了对数量众多的非被支配解进行有效的拥挤控制并提升种群的多样性, 本文在提出张角概念的基础上设计了一种新的拥挤控制策略(Congestion control strategy based on open angle, CCSOA),它的时间复杂度并不会随着目标维数的增加而增大. 与目前优秀的进化多目标优化(Evolutionary multiobjective optimization, EMO)算法IBEA (Indicator-based evolutionary algorithm)、NSGAIII (Nondominated sorting genetic algorithm III)和GrEA (Grid-based evolutionary algorithm)的比较结果表明, 融合了CCSOA的高维多目标优化算法在收敛效果和解集分布的均匀性两个方面均有较大的优势.
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出版历程
  • 收稿日期:  2014-07-30
  • 修回日期:  2015-02-02
  • 刊出日期:  2015-06-20

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