基于遗传算法的钢筋混凝土柱优化设计

IF 0.6 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES
Isabella Silva Menezes, Vinicius Navarro Varela Tinoco, A. Christoforo, Florisvaldo Cardozo Bomfim Junior, Tarniê Vilela Nunes Narques
{"title":"基于遗传算法的钢筋混凝土柱优化设计","authors":"Isabella Silva Menezes, Vinicius Navarro Varela Tinoco, A. Christoforo, Florisvaldo Cardozo Bomfim Junior, Tarniê Vilela Nunes Narques","doi":"10.4025/actascitechnol.v45i1.61562","DOIUrl":null,"url":null,"abstract":"Reinforced concrete is an essential material in the modern world, and the use of genetic algorithms that aim at the optimization of the structures of this material is an increasingly widespread tool. The objective of the present work was to propose a method by means of a Genetic Algorithm to find the optimized geometry of a rectangular reinforced concrete column based on its cost. The two main parts of the work were developed as: a geometry verification algorithm that received height, base, layers in x and y directions, diameters of transverse and longitudinal steel rebar as the main parameters of the proposed sections, and a genetic algorithm that generated 240 random populations and selected them, crossed among them and then generated new 100 generations of individuals, followed by selection of optimized ones by its penalized cost. The generations had more and more favorable individuals and it was possible to determine an optimized geometry for the proposed example. It is, therefore, concluded that genetic algorithms are useful tools for optimizing reinforced concrete parts with multiple parameters. The proposed algorithm methodology really checks and selects the best individuals for the sections proposed by engineers, and larger initial populations are essential to find a minimum global cost among the different options.","PeriodicalId":7140,"journal":{"name":"Acta Scientiarum-technology","volume":"2012 1","pages":""},"PeriodicalIF":0.6000,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Optimization of reinforced concrete columns via genetic algorithm\",\"authors\":\"Isabella Silva Menezes, Vinicius Navarro Varela Tinoco, A. Christoforo, Florisvaldo Cardozo Bomfim Junior, Tarniê Vilela Nunes Narques\",\"doi\":\"10.4025/actascitechnol.v45i1.61562\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reinforced concrete is an essential material in the modern world, and the use of genetic algorithms that aim at the optimization of the structures of this material is an increasingly widespread tool. The objective of the present work was to propose a method by means of a Genetic Algorithm to find the optimized geometry of a rectangular reinforced concrete column based on its cost. The two main parts of the work were developed as: a geometry verification algorithm that received height, base, layers in x and y directions, diameters of transverse and longitudinal steel rebar as the main parameters of the proposed sections, and a genetic algorithm that generated 240 random populations and selected them, crossed among them and then generated new 100 generations of individuals, followed by selection of optimized ones by its penalized cost. The generations had more and more favorable individuals and it was possible to determine an optimized geometry for the proposed example. It is, therefore, concluded that genetic algorithms are useful tools for optimizing reinforced concrete parts with multiple parameters. The proposed algorithm methodology really checks and selects the best individuals for the sections proposed by engineers, and larger initial populations are essential to find a minimum global cost among the different options.\",\"PeriodicalId\":7140,\"journal\":{\"name\":\"Acta Scientiarum-technology\",\"volume\":\"2012 1\",\"pages\":\"\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2022-12-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta Scientiarum-technology\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.4025/actascitechnol.v45i1.61562\",\"RegionNum\":4,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Scientiarum-technology","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.4025/actascitechnol.v45i1.61562","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 2

摘要

钢筋混凝土是现代世界中必不可少的材料,使用遗传算法来优化这种材料的结构是一种越来越广泛的工具。本文的目的是提出一种基于成本的矩形钢筋混凝土柱的优化几何形状的遗传算法。工作的两个主要部分是:一个几何验证算法,它以高度、基底、x和y方向的层数、横向和纵向钢筋的直径作为建议截面的主要参数;一个遗传算法,它产生240个随机种群并选择它们,在它们之间交叉,然后产生新的100代个体,然后根据惩罚成本选择最优的个体。这几代人有越来越多的有利个体,可以为所提出的例子确定一个优化的几何形状。因此,遗传算法是优化多参数钢筋混凝土零件的有效工具。所提出的算法方法确实为工程师提出的部分检查并选择最佳个体,并且较大的初始种群对于在不同选项中找到最小的全局成本是必不可少的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of reinforced concrete columns via genetic algorithm
Reinforced concrete is an essential material in the modern world, and the use of genetic algorithms that aim at the optimization of the structures of this material is an increasingly widespread tool. The objective of the present work was to propose a method by means of a Genetic Algorithm to find the optimized geometry of a rectangular reinforced concrete column based on its cost. The two main parts of the work were developed as: a geometry verification algorithm that received height, base, layers in x and y directions, diameters of transverse and longitudinal steel rebar as the main parameters of the proposed sections, and a genetic algorithm that generated 240 random populations and selected them, crossed among them and then generated new 100 generations of individuals, followed by selection of optimized ones by its penalized cost. The generations had more and more favorable individuals and it was possible to determine an optimized geometry for the proposed example. It is, therefore, concluded that genetic algorithms are useful tools for optimizing reinforced concrete parts with multiple parameters. The proposed algorithm methodology really checks and selects the best individuals for the sections proposed by engineers, and larger initial populations are essential to find a minimum global cost among the different options.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Acta Scientiarum-technology
Acta Scientiarum-technology 综合性期刊-综合性期刊
CiteScore
1.40
自引率
12.50%
发文量
60
审稿时长
6-12 weeks
期刊介绍: The journal publishes original articles in all areas of Technology, including: Engineerings, Physics, Chemistry, Mathematics, Statistics, Geosciences and Computation Sciences. To establish the public inscription of knowledge and its preservation; To publish results of research comprising ideas and new scientific suggestions; To publicize worldwide information and knowledge produced by the scientific community; To speech the process of scientific communication in Technology.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信