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題 名 | Discrete Optimization of Truss Structures Using Genetic Algorithms with Adaptation=以適應遺傳演算法作桁架結構離散最佳化 |
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作 者 | 葉怡成; | 書刊名 | 中國土木水利工程學刊 |
卷 期 | 10:1 1998.03[民87.03] |
頁 次 | 頁109-116 |
分類號 | 441.117 |
關鍵詞 | 結構最佳化設計; 離散最佳化; 遺傳演算法; 滿載應力設計法; Structural optimization; Discrete optimization; Genetic algorithms; Fully stressed design; |
語 文 | 英文(English) |
中文摘要 | 大多數實用的結構最佳化設計須考慮設計變數為離散的數值。遺傳演算法是一 種模擬生物演化機制的最佳化方法,其架構可直接對應離散結構最佳化問題。雖然它是一 個相當強健的方法,但它也是一個計算密集以致於比其它方法慢的方法。為了提昇收斂速 度,本文提出一個結合生物演化機制中「適應」概念的混合法。滿載應力設計法將擔任適 應的角色。數值例題顯示,即使是在位移限制主控的情況下,(1)混合法所得的解答較優 (2)混合法的解答品質穩定性較優(3)混合法的解答品質改進幅度正比於結構尺度(4)混合 法的收斂速度較優。 |
英文摘要 | Because structural sections must usually be selected from a limited set of sections commercially available, the design variables of structural optimization are discrete in nature. Genetic algorithm (GA) is a new optimization paradigm that models a natural evolution mechanism. The framework of GA naturally corresponds to an discrete optimization problem. Although GA is robust, it is also computation-intensive and hence slower than other methods. To speed up the rate of convergence, this paper proposes a hybrid GA that combines the concept of adaptation. Fully stressed design is employed to play as the role of adaptation. Numerical examples show that even though the displacement constraints are active, (1) both average weight and minimum weight obtained by hybrid GA are less than that obtained by pure GA, (2) hybrid GA is more stable than pure GA, (3) the improvement by hybrid GA is approximately proportional to the scale of structures, and (4) the speed of convergence of hybrid GA is superior to that of pure GA. |
本系統中英文摘要資訊取自各篇刊載內容。