應用粒子群最佳化演算法於結構拓樸最佳化

Structural topology optimization using particle swarm optimization algorithm

林玉書(Yu-shu Lin)

指導教授 ： 陸冠群

大同大學/工程學院/機械工程學系所/碩士(2009年)

摘要

粒子群最佳化法是近期興起的一種仿生演算法，它仿照鳥類群體行為去求解最佳化問題，本研究應用在連續結構拓樸問題上。首先描述粒子群最佳化法和二進位粒子群最佳化法的概要，再詳細介紹二進位粒子群最佳化法要如何演算結構拓樸。隨後，介紹本研究所提出的兩種粒子群最佳化法，改善式粒子群最佳化法和邏輯式粒子最佳化法的概念，去說明如何演算結構拓樸問題。使用四個結構拓樸的標準範例去找尋結構拓樸的多樣性，驗證所提出的演算法是有效性的。由結果可以觀察出本研究所提出的粒子群最佳化法是能有效處理拓樸問題，它能夠找出多樣性的結構拓樸。

關鍵字

結構拓樸最佳化 ； 粒子群最佳化

並列摘要

The particle swarm optimization (PSO) algorithm, a relatively recent bio-inspired approach to solve combinatorial optimization problems mimicking the social behavior of birds flocking, is applied to problems of continuum structural topology design. An overview of the PSO and binary PSO algorithms are first described. A discretized topology design representation and the method for mapping binary particle into this representation are then detailed. Subsequently, modified binary PSO algorithm and logic binary PSO algorithm adopt the concept of genotype-phenotype representation are illustrated. Several well-studied examples from structural topology optimization problems of minimum weight and minimum compliance are used to demonstrate its efficiency and versatility. The results indicate the effectiveness of the proposed algorithm and its ability to find families of structural topologies.

並列關鍵字

structural topology optimization ； binary particles swarm optimization

參考文獻

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