一种改进的鲁棒多目标优化方法. 徐鸣, 马龙华, 顾江萍, 黄跃进, & 沈希 控制与决策, 28(8):1178–1182+1189, 2013. 12 citations(CNKI)[2023-2-22]\textless北大核心, EI, CSCD\textgreaterPaper doi abstract bibtex 针对在解决某些复杂多目标优化问题过程中,所得到的Pareto最优解易受设计参数或环境参数扰动的影响.引入了鲁棒的概念并提出一种改进的鲁棒多目标优化方法,它利用了经典的基于适应度函数期望和方差方法各白的优势,有效地将两���方法结合在��起.为了实现该方法,给出一种基于粒子群优化算法的多目标优化算法.仿真实例结果表明,所给出的方法能够得到更为鲁棒的Pareto最优解.
@article{__2013,
title = {一种改进的鲁棒多目标优化方法},
volume = {28},
issn = {1001-0920},
url = {https://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFD&dbname=CJFD2013&filename=KZYC201308011&v=},
doi = {10.13195/j.kzyjc.2013.08.004},
abstract = {针对在解决某些复杂多目标优化问题过程中,所得到的Pareto最优解易受设计参数或环境参数扰动的影响.引入了鲁棒的概念并提出一种改进的鲁棒多目标优化方法,它利用了经典的基于适应度函数期望和方差方法各白的优势,有效地将两���方法结合在��起.为了实现该方法,给出一种基于粒子群优化算法的多目标优化算法.仿真实例结果表明,所给出的方法能够得到更为鲁棒的Pareto最优解.},
language = {中文;},
number = {8},
journal = {控制与决策},
author = {徐鸣 and 马龙华 and 顾江萍 and 黄跃进 and 沈希},
year = {2013},
note = {12 citations(CNKI)[2023-2-22]{\textless}北大核心, EI, CSCD{\textgreater}},
keywords = {/unread, multi-objective optimization, robust optimization, 参数扰动, 多目标优化, 鲁棒优化 parameter perturbation},
pages = {1178--1182+1189},
}
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