关键词:

GAIM, 优化, Kriging代理模型, APSO算法

Abstract:

For the gas-assisted injection molding process, it is hard to find the explicit relationship between the depth of gas penetration and processing parameters.In this paper, an optimization strategy based on Kriging metamodel and adaptive particle swarm optimization (APSO) algorithm was developed.The Kriging metamodel was adopted to approximate the nonlinear relationship between processing parameters and the depth of gas penetration, and the APSO algorithm was adopted to carry out the optimization procedure.Moreover, such strategy was used for the parameter optimization of a real auto rear view mirror, in which the depth of gas penetration was set as the optimization objective.It was shown that the presented optimization strategy based on Kriging metamodel and APSO algorithm could achieve higher solving accuracy and fast convergence rate for those small sample size problems.

Key words:

GAIM, 优化, Kriging代理模型, APSO算法