Optimization of Structures Using Improved Genetic Algorithms for Discrete Variables

被引：0

作者：

Tian, Yuan ^{[1
]}

Shi, Qingxuan ^{[1
]}

Zhu, Chaoyan ^{[2
]}

机构：

[1] Xian Univ Architecture & Technol, Sch Civil Engn, Xian 710055, Peoples R China

[2] Liaoning Univ Technol, Sch Civil Engn, Jinzhou 121001, Peoples R China

来源：

ADVANCES IN STRUCTURES, PTS 1-5 | 2011年 / 163-167卷

基金：

中国国家自然科学基金;

关键词：

Discrete Variable; Structural Optimization; Genetic Algorithm; Improved Genetic Algrothm;

D O I：

10.4021/www.scientific.net/AMR.163-167.2437

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Genetic algorithms (GA) have been shown to be very effective optimization tools for a number of engineering problems. Genetic algorithms which are based upon the principles of Darwinian evolution explores the region of the whole solution space and can obtain the golbal optimum. This paper introduces the standard GA and the forward-and-back search algorithms (FBSA) and demonstrates the use of improved genetic algorithms (IGA) for structure optimization of discrete variables. The mathematical model of structural optimization is derived. A 10-bar benchmarl: example is studied, the result shows that IGA, as an efficient method,can be applied to structure optimization of discrete variables.

引用

页码：2437 / 2440

页数：4