Optimal Building Frame Column Design Based on the Genetic Algorithm

• 作者: Chan Gao Tao Shen Yukari Nagai
• 来源期刊: 计算机、材料和连续体(英文)
• 学科: 工学
• 关键词: Structure optimization GENETIC algorithm CONCURRENT COMPUTATION CONCEPTUAL DESIGN simulation experiment.
• 年，卷（期）: 2019,（3）
• 页码范围: 641-651
• 页数: 11页
• 分类号: TP3

摘要

Building structure is like the skeleton of the building,it bears the effects of various forces and forms a supporting system,which is the material basis on which the building depends.Hence building structure design is a vital part in architecture design,architects often explore novel applications of their technologies for building structure innovation.However,such searches relied on experiences,expertise or gut feeling.In this paper,a new design method for the optimal building frame column design based on the genetic algorithm is proposed.First of all,in order to construct the optimal model of the building frame column,building units are divided into three categories in general:building bottom,main building and building roof.Secondly,the genetic algorithm is introduced to optimize the building frame column.In the meantime,a PGA-Skeleton based concurrent genetic algorithm design plan is proposed to improve the optimization efficiency of the genetic algorithm.Finally,effectiveness of the mentioned algorithm is verified through the simulation experiment.