张国晨,樊凯翔,王浩,秦淑芬,孙超利

• 1:太原科技大学计算机科学与技术学院
• 2:太原科技大学电子信息工程学院

摘要(Abstract)：

代理模型辅助的多目标进化算法广泛用于解决计算费时的多目标优化问题，然而现有的大部分建模方法都是为了嵌入到特定算法而设计的，适应于其他算法的能力并不强，为了能够依据数据特征自适应的建立模型，提出了一种基于自适应模型选择的建模方法。该方法的主要思想为：依据每个目标函数的样本特征，自适应的选择样本建立全局模型或者局部模型。为了验证所提出建模的方法的有效性，将提出的建模方法应用于基于高斯过程辅助的双存档费时多目标优化算法(KAT2)和基于高斯过程辅助的参考向量引导的费时多目标优化算法(K-RVEA),并且在DTLZ测试函数进行测试。通过实验证明，提出的建模方法可以有效的解决费时多目标优化问题。

关键词(KeyWords)： 模型辅助的进化算法;多目标优化;克里金模型;自适应

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金(61876123);; 山西省自然科学基金(201901D111264)

作者(Author): 张国晨,樊凯翔,王浩,秦淑芬,孙超利

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