GENETIC ALGORITHMS WITH LOCAL IMPROVEMENT FOR COMPOSITE LAMINATE DESIGN

被引：116

作者：

KOGISO, N

WATSON, LT

GURDAL, Z

HAFTKA, RT

机构：

[1] Department of Aerospace Engineering, Graduate School, University of Osaka Prefecture, Sakai, 593

[2] Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, 24061, VA

[3] Department of Engineering Science and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, 24061, VA

[4] Department of Aerospace and Ocean Engineering, Virginia Polytechnic Institute and State University, Blacksburg, 24061, VA

来源：

STRUCTURAL OPTIMIZATION | 1994年 / 7卷 / 04期

关键词：

D O I：

10.1007/BF01743714

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper describes the application of a genetic algorithm to the stacking sequence optimization of a laminated composite plate for buckling load maximization. Two approaches for reducing the number of analyses required by the genetic algorithm are described. First, a binary tree is used to store designs, affording an efficient way to retrieve them and thereby avoid repeated analyses of designs that appeared in previous generations. Second, a local improvement scheme based on approximations in terms of lamination parameters is introduced. Two lamination parameters are sufficient to define the flexural stiffness and hence the buckling load of a balanced, symmetrically laminated plate. Results were obtained for rectangular graphite-epoxy plates under biaxial in-plane loading. The proposed improvements are shown to reduce significantly the number of analyses required for the genetic optimization.

引用

页码：207 / 218

页数：12

共 16 条

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