An effective Kriging-based Constrained Opmization Algorithm by Global and Local Sampling in Feasible

来源 :Asian Congress of Structural and Multidisciplinary Optimizat | 被引量 : 0次 | 上传用户：jinke1983

【摘要】

：

Kriging model is widely used in structural and multidisciplinary optimization.A few algorithms can deal with the expensive objective function and constraint functions,but the computational efficiency

【作者】

：

Tianzeng Tao Guozhong Zhao Shanhong Ren

【机构】

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Dept.of Engineering Mechanics, Dalian University of Technology, 116023, Dalian, China

【出处】

：

Asian Congress of Structural and Multidisciplinary Optimizat

【发表日期】

：

2018年11期

【关键词】

：

Kriging Constrained optimization Feasible region sampling Objective local region

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　　Kriging model is widely used in structural and multidisciplinary optimization.A few algorithms can deal with the expensive objective function and constraint functions,but the computational efficiency of these algorithms has much room for promotion.Considering the case,an Efficient Kriging-based Constrained Optimization (EKCO) algorithm is proposed to handle these functions with limited sample points.The EKCO algorithm contains three phases.In phase 1,a Feasible Region Sampling (FRS) criterion is introduced to determine the feasible region.

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