From package and design surfaces to optimization - how to apply shape optimization under geometrical constraints
نویسندگان
چکیده
منابع مشابه
How to prove existence in shape optimization
This paper deals with the existence question in optimal design. We present a general variational technique for proving existence, and give several examples concerning functionals of eigenvalues and of energy type. In particular, we show how the isoperimetric problem for the Dirichlet eigenvalues of an elliptic operator of general order fit into this frame.
متن کاملAdjoint shape optimization applied to electromagnetic design.
We present an adjoint-based optimization for electromagnetic design. It embeds commercial Maxwell solvers within a steepest-descent inverse-design optimization algorithm. The adjoint approach calculates shape derivatives at all points in space, but requires only two "forward" simulations. Geometrical shape parameterization is by the level set method. Our adjoint design optimization is applied t...
متن کاملInvestment optimization under constraints
We analyze general stochastic optimization financial problems under constraints in a general framework, which includes financial models with some “imperfection”, such as constrained portfolios, labor income, random endowment and large investor models. By using general optional decomposition under constraints in a multiplicative form, we first develop a dual formulation under minimal assumption ...
متن کاملOptimization Under Unknown Constraints
Optimization of complex functions, such as the output of computer simulators, is a difficult task that has received much attention in the literature. A less studied problem is that of optimization under unknown constraints, i.e., when the simulator must be invoked both to determine the typical real-valued response and to determine if a constraint has been violated, either for physical or policy...
متن کاملBayesian optimization with shape constraints
In typical applications of Bayesian optimization, minimal assumptions are made about the objective function being optimized. This is true even when researchers have prior information about the shape of the function with respect to one or more argument. We make the case that shape constraints are often appropriate in at least two important application areas of Bayesian optimization: (1) hyperpar...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Procedia CIRP
سال: 2021
ISSN: 2212-8271
DOI: 10.1016/j.procir.2021.05.118