最优形状设计问题的数值方法比较

Manfred Laumen
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引用次数: 3

摘要

将若干最优形状设计问题定义为带等式约束的最小化问题,该问题由边值问题给出。映射方法将其转换为固定域上的特定控制问题。将这一最优控制问题离散化通常会导致大规模的优化公式,而相应的求解方法需要求解许多边值问题。尽管这是一个有趣的数值挑战,但到目前为止,比较不同数值优化方法的研究还很少,包括最优形状设计问题的二阶方法。本文针对一类最优形状设计问题,导出了牛顿法和拟牛顿法的几种变体,并与常用的梯度法进行了比较。详细讨论了这些方法及其嵌套迭代版本的优缺点。各种数值经验强调了选择正确优化的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Comparison of Numerical Methods for Optimal Shape Design Problems
Several optimal shape design problems are defined as a minimization problem with an equality constraint that is given by a boundary value problem. The mapping method transforms this to a specific control problem on a fixed domain. Discretizing this optimal control problem normally leads to a large scale optimization formulation where the corresponding solution methods are characterized by the requirement of solving many boundary value problems. In spite of this interesting numerical challenge, until now less research has been done on comparing different numerical optimization approaches including second order methods for optimal shape design problems. In this paper, Newton's and several variants of quasi-Newton methods are derived for a class of optimal shape design problems and compared to the commonly used gradient method. The pros and cons of these methods plus their nested iteration versions are discussed in detail. Various numerical experiences underline the importance of choosing the right optimizat...
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