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

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 cstr: 32138.14.j.aas.2015.c140555

1.
福建师范大学数学与计算机科学学院福州 350007

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

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- 被引次数: 0
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

Many-objective Optimization Integrating Open Angle Based Congestion Control Strategy

1.
College of Mathmatic and Computer Science, Fujian Normal University, Fuzhou 350007

Funds:

Supported by National Natural Science Foundation of China (61175123)

摘要

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.
- 高维多目标优化 /
- 进化算法 /
- 拥挤控制 /
- 张角
Abstract: For the many-objective optimization problem, the proportion of non-dominated individuals increases dramatically with the increase of target dimension, which may seriously reduce the population evolutionary pressure. In order to efficiently control the congestion among the very lagre numbers of non-dominated solutions and improve its diversity, this paper firstly defines the concept of open angle, based on which a novel congestion control strategy is proposed, called CCSOA (Congestion control strategy based on open angle) here. It is time complexity will not increase with the increasing target dimension. Compared with some well-known algorithms such as IBEA (Indicator-based evolutionary algorithm), NSGAIII (Nondominated sorting genetic algorithm III) and GrEA (Grid-based evolutionary algorithm), the many-objective optimization algorithm integrated with CCSOA has better convergence and remains better diversity and uniformity.
- Many-objective optimization /
- evolutionary algorithm /
- congestion control /
- open angle

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参考文献(29)

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