A proper infill sampling strategy for improving the speed performance of a Surrogate-Assisted Evolutionary Algorithm

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• 作者：Loris Vincenzi ; ^{loris.vincenzi@unimore.it" class="auth_mail" title="E-mail the corresponding author} ; Paola Gambarelli
• 关键词：Surrogate model ; Evolutionary algorithm ; Model updating ; Differential evolution ; Infill sampling strategy
• 刊名：Computers & Structures
• 出版年：2017
• 出版时间：1 January 2017
• 年：2017
• 卷：178
• 期：Complete
• 页码：58-70
• 全文大小：2316 K

文摘

In the present paper, an improved Surrogate-Assisted Evolutionary Algorithm is proposed. It combines the Differential Evolution algorithm with a quadratic surrogate approximation and a proper infill sampling strategy to choose appropriate sample points. The selection of the new candidate points is arranged to enhance both the local accuracy and the global optimum search. A comparison between performances of different evolutionary algorithms is carried out by searching the global minimum of two benchmark functions, by solving a dynamic identification problem of a three floor frame and by calibrating the non-linear stress-crack opening relation for Fibre-Reinforced Concrete specimens starting from experimental data.