引用本文: | 罗文彩,黄奕勇,杨维维,等.子空间分解与淘汰优化方法[J].国防科技大学学报,2011,33(5):41-44,53.[点击复制] |
LUO Wencai,HUANG Yiyong,YANG Weiwei,et al.ubspace Decomposition and Discarding Optimization[J].Journal of National University of Defense Technology,2011,33(5):41-44,53[点击复制] |
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子空间分解与淘汰优化方法 |
罗文彩, 黄奕勇, 杨维维, 刘常青 |
(国防科技大学 航天与材料工程学院,湖南 长沙 410073)
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摘要: |
提出一种新的多学科设计优化方法,即子空间分解与淘汰优化方法。该方法通过子空间的分解和淘汰,提高剩余子空间的近似模型精度,基于子空间近似模型优化获取最优解。首先,基于设计空间近似模型获取最优解,如果近似模型达到满意精度,则终止优化;否则将设计空间分解为多个子空间。然后,各子空间基于近似模型优化,如果子空间没有可能获得优于当前最优解的最优解,则淘汰;如果子空间近似模型的精度达到满意精度,则子空间不再分解;如果子空间没有获得满意精度但有可能获得更优解,则将子空间分解为更小的子空间。该方法的优化计算时间与设计变量维数和设计空间大小密切相关。算例研究表明该优化方法在计算时间和全局优化解方面具有良好性能。 |
关键词: 子空间分解 子空间淘汰 近似模型 |
DOI: |
投稿日期:2011-04-11 |
基金项目:国家自然科学基金资助项目(50975280);教育部新世纪优秀人才支持计划资助项目(NCET-08-0149);国防科技大学科研计划资助项目(JC-08-01-07) |
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ubspace Decomposition and Discarding Optimization |
LUO Wencai, HUANG Yiyong, YANG Weiwei, LIU Changqing |
(College of Aerospace and Materials Engineering, National Univ. of Defense Technology, Changsha 410073, China)
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Abstract: |
A new MDO algorithm named as Subspace Decomposition and Discarding Optimization (SDDO) is advanced here. The optimization is based on the approximation model, of which the main idea is based on the subspace decomposition and discarding. Firstly, the approximation model of a MDO problem was carried on its design space. If the precision of approximation model reaches a satisfying precision, this optimization procedure will be terminated. Otherwise, the design space will be decomposed into two or more subspaces. Then, the optimization will be carried on the approximation of these subspaces. If the subspace has no promise to get better optimization result than the optimum reached by other subspaces, the subspace will be discarded. If the subspace approximation precision has reached a satisfying precision, this subspace will not be decomposed into smaller subspace. If the subspace has not reached a satisfying precision and has promise to get better optima, this subspace will be decomposed into smaller subspaces. The calculation time of this process is related to the numbers of design variables and design space. Function optimization examples show that this optimization algorithm has good performance on calculation time and global optima. |
Keywords: subspace decomposition subspace discarding approximation model |
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