A Multi-Objective Evolutionary Algorithm Based on Principal Component Analysis and Grid Division
Mei Ma, Hecheng Li, Jing Huang · 2018
In order to effectively solve the many objective optimization problems (MaOPs), a new multi-objective evolutionary algorithm is proposed. Firstly, utilizes the principal component analysis (PCA) to reduce the dimension of objective space. The main idea is do a correlation analysis between objectives. Secondly, puts forward a new grid division method. In the course of dividing, make sure all grid sizes are equal. The simulation illustrates the efficiency of the proposed algorithm.