A Riemannian View on Shape Optimization
نویسنده
چکیده
Shape optimization based on the shape calculus is numerically mostly performed by means of steepest descent methods. This paper provides a novel framework to analyze shapeNewton optimization methods by exploiting a Riemannian perspective. A Riemannian shape Hessian is defined yielding often sought properties like symmetry and quadratic convergence for Newton optimization methods.
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عنوان ژورنال:
- Foundations of Computational Mathematics
دوره 14 شماره
صفحات -
تاریخ انتشار 2014