Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/10548
標題: 粒子群演算法於結構構件之最佳化斷面
Particle Swarm Optimization for cross-sectional size of frame-structures
作者: 曾乙申
Tzeng, yi-shen
關鍵字: 粒子群演算法
Particle Swarm Optimization
最佳斷面
best-cross sectional
出版社: 土木工程學系所
引用: [1] Adeli,H., Kumar,S.“Distrbuted Genetic Algorithm for Structural Optimization.”Journal of Aerospace Engineering.1995. [2] Camp,C., Pezeshk,S., Cao,G..“Optimized Design of Two-Dimensional Structures Using a Genetic Algorithm.”J. Struct.Engrg.1998. [3] Hager,K., Balling,R.. “New Approach for Discrete Structural Optimization.”Journal of Structural Engineering.1998. [4] Kennedy,J., Eberhart,R. “Particle swarm optimization”1995. [5] Pezeshk,S., Camp,C.V.,Chen,D.“Design if Nonlinear Framed Structures Using Genetic Optimization.”J.Struct.Engrg.2000. [6] Soegiarso,R., Adeli,H.“Optimum Load and Resistance Factor Design of Steel Space-Frame Structures.”J. Struct. Engrg.1997. [7] 紀震,廖惠連,吳青華編著“粒子群算法及應用”科學出版社,2009. [8]內政部營建署“中華民國建築物基礎構造設計規範”,2011. [9]簡仲唯“粒子群於結構桿件之最佳化設計”國立中興大學,2012. [10]鄭博育“啟發式桁架斷面尺寸最佳化設計”國立交通大學,2005. [11]林玉書“應用粒子群最佳化演算法於結構拓樸最佳化”,大同大學,2009.
摘要: 本文研究目的,利用粒子群演算法分析鋼結構之最佳斷面。考慮結構受各種邊界條件之影響。 利用粒子群演算法,求得結構受各種邊界條件影響之最佳斷面。結果顯示,當容許位移為1 cm 以及容許沉陷為2.5 cm時,所求得結構構件之最佳斷面均在合理範圍內。
The purpose of this study is to utilize particle swarm optimization approach for the optimization of steel structure cross-section. The effect of structure on various boundary conditions is considered. Using particle swarm optimization technique, the best-cross sections of steel structural members on various boundary conditions are obtained. If allowable lateral deflection is 1 cm and allowable subsidence is 2.5 cm, it is shown that the optimized cross-sectional areas of structural members are reasonable.
URI: http://hdl.handle.net/11455/10548
其他識別: U0005-2808201317160100
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-2808201317160100
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