摘要
提出了同时考虑预测响应值以及期望改善准则的改进高效全局优化(IMEGO)算法。IMEGO算法在增加样本点提高模型精度的迭代过程中,优先考虑模型的最优解,同时增加更加严谨的收敛准则。以1个一维测试函数和3个二维测试函数为例,将该优化方法与传统的高效全局优化算法(EGO)方法进行比较。结果表明,IMEGO算法能有效搜索到全局最优解。将其应用于显示器外壳注塑制品的成型工艺参数优化,结果显示IMEGO方法具有较好的工程实际意义。
IMEGO algorithm proposed to conquer premature convergence might occur in EGO algorithm when the objective function varied in a large range in this study.The optimal solution of the kriging model for each iteration was preferred and stopping criteria on expected improvement was added in the IMEGO algorithm.The IEGO was compared with traditional EGO through a onevariable test function and three two-variables test functions,it was then shown that the improved EGO could effectively search the global optimum.The IMEGO was used to optimize injection molding process parameters for covers of liquid crystal display parts and the results showed that it had a good application in engineering.
出处
《中国塑料》
CAS
CSCD
北大核心
2015年第4期88-92,共5页
China Plastics
关键词
注射成型
高效全局优化
期望改善
injection molding
efficient global optimization
expected improvement
