首页 | 官方网站   微博 | 高级检索  
     

基于遗传算法的密肋复合墙体多目标优化设计方法研究
引用本文:侯莉娜,姚谦峰,黄炜,荆罡,陈国新.基于遗传算法的密肋复合墙体多目标优化设计方法研究[J].工业建筑,2009,39(10).
作者姓名:侯莉娜  姚谦峰  黄炜  荆罡  陈国新
作者单位:西安建筑科技大学土木工程学院,西安,710055
基金项目:国家自然科学基金,国家科技支撑项目,陕西省13115项目,陕西省教育厅自然科学专项基金 
摘    要:密肋复合墙体是密肋壁板结构体系的主要受力构件,墙体的优化设计方法研究是结构体系设计理论的重要组成部分。在前期研究的基础上,建立综合考虑密肋复合墙体安全性(墙体斜截面抗剪承载力)与经济性(墙体造价)的多目标优化设计数学模型,并采用遗传算法进行优化计算,最后给出了计算算例。理论分析与计算结果表明:将多目标优化设计方法用于密肋复合墙体的优化设计中,可使各个分目标都较为满意,兼顾了墙体安全性与经济性两方面的要求;方法合理、可行,对密肋复合墙体的设计有一定参考意义。

关 键 词:密肋复合墙体  多目标优化设计  遗传算法

MULTI-OBJECTIVE OPTIMIZATION DESIGN METHOD OF MULTI-RIBBED COMPOSITE WALL BASED ON GA
Hou Lina,Yao Qianfeng,Huang Wei,Jing Gang,Chen Guoxin.MULTI-OBJECTIVE OPTIMIZATION DESIGN METHOD OF MULTI-RIBBED COMPOSITE WALL BASED ON GA[J].Industrial Construction,2009,39(10).
Authors:Hou Lina  Yao Qianfeng  Huang Wei  Jing Gang  Chen Guoxin
Abstract:Multi-ribbed composite wall is the main load-bearing member in the multi-ribbed slab structure(MRSS).The study on the optimization design method of the wall is an important part of the design theory for the structural system.It is discussed the multi-objective optimization design method of the multiribbed composite wall.The multi-objective optimization design mathematical model which takes both the security(shear resistance of the wall) and economy(cost of the wall) into consideration is established.Then the genetic algorithm(GA) is employed to solve the proposed model.At the same time,a case of optimization design is given.Theoretical analysis and calculated results show that applying the multi-objective optimization design method to the optimization design of the multi-ribbed composite wall can make every objective satisfactory and give consideration to both the security and economy of the wall,and this method was found to be reasonable,practicable and have some meaning to the practical engineering.
Keywords:Multi-Ribbed Composite Wall  Multi-objective Optimization Design  Genetic Algorithm
本文献已被 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司    京ICP备09084417号-23

京公网安备 11010802026262号