- Risk|Averse PDE|Constrained Optimization Using the Conditional ...🔍
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- Risk|averse PDE|constrained optimization using the conditional ...🔍
- An Introduction to Risk|Averse PDE|Constrained Optimization🔍
- Existence and Optimality Conditions for Risk|Averse PDE ...🔍
- ADAPTIVE LOCAL REDUCED BASIS METHOD FOR RISK|AVERSE ...🔍
- Risk|Averse PDE|Constrained Optimization using the ...🔍
- Risk|Averse PDE|Constrained Optimization using the Conditional ...🔍
Risk|Averse PDE|Constrained Optimization Using the ...
Risk-Averse PDE-Constrained Optimization Using the Conditional ...
In this work, we introduce a general framework for analyzing risk-averse optimization problems constrained by partial differential equations (PDEs). In ...
Risk-Averse PDE-Constrained Optimization Using the ... - OPUS
In this work, we develop approximations and theory for the conditional value-at-risk (CVaR) applied to optimization problems constrained by partial differential ...
Risk-averse PDE-constrained optimization using the conditional ...
Uncertainty is inevitable when solving science and engineering application problems. In the face of uncertainty, it is essential to determine ...
Risk-Averse PDE-Constrained Optimization Using the Conditional ...
In this work, we consider a class of PDE-constrained optimization problems in which the PDE coefficients and inputs may be uncertain.
Risk-Averse PDE-Constrained Optimization Using the Conditional ...
sample-based methods include (quasi-)Monte Carlo and stochastic collocation or de- terministic quadrature methods [3, 26, 25, 44]. Optimizing ...
An Introduction to Risk-Averse PDE-Constrained Optimization
“PDE”-part: F(x) requires the solution of a PDE with input x. “Random”-part: cannot evaluate F(x) or even F(xh) xh ∈ Xh.
Existence and Optimality Conditions for Risk-Averse PDE ...
Here in this paper, we introduce a general framework for analyzing risk-averse optimization problems constrained by partial differential equations (PDEs). In ...
ADAPTIVE LOCAL REDUCED BASIS METHOD FOR RISK-AVERSE ...
Many physical systems are modeled using partial dierential equations (PDEs) with uncertain or random inputs ... risk-averse optimization problems with PDE ...
Risk-Averse PDE-Constrained Optimization using the ... - OSTI.GOV
Risk-Averse PDE-Constrained Optimization using the Conditional Value-At-Risk. Conference · Sat Nov 01 00:00:00 EDT 2014 · OSTI ID:1145907. Kouri ...
Risk-Averse PDE-Constrained Optimization using the Conditional ...
Risk-Averse PDE-Constrained Optimization using the Conditional Value-at-Risk ... Uncertainty is inevitable when solving science and engineering ...
Smoothing techniques for risk-averse PDE-constrained optimization
In this talk, I formulate such problems as risk-averse optimization problems in Banach space. For many popular measures of risk such as coherent risk measures, ...
Risk-Averse PDE-Constrained Optimization using the Conditional ...
Risk-Averse PDE-Constrained Optimization using the Conditional Value-At-Risk. Kouri, Drew P. Abstract not provided. Additional Metadata. SAND Number. SAND2014 ...
Newton-Based Methods for the Numerical Solution of Risk-Averse ...
Newton-Based Methods for the Numerical Solution of Risk-Averse. PDE-Constrained Optimization Problems. Mae Markowski, Advisor: Matthias Heinkenschloss.
Functional Constrained Optimization for Risk Aversion and Sparsity ...
Properly balancing these potentially conflicting requirements entails the formulation of functional constrained optimization with either convex ...
Efficient Solution of Smoothed Risk-Averse PDE-Constrained ...
This thesis focuses on the development and implementation of structure-exploiting numerical methods for more efficiently and inexpensively solving risk-averse ...
Existence and Optimality Conditions for Risk-Averse PDE ...
... PDE-constrained optimization under uncertainty is a rapidly growing field with a number of recent contributions in theory [6,24, 25, 27] ...
A Locally Adapted Reduced-Basis Method for Solving Risk-Averse ...
The numerical solution of risk-averse optimization problems constrained by PDEs requires substantial computational effort resulting from the discretization ...
Existence and Optimality Conditions for Risk-Averse PDE ...
This work introduces a general framework for analyzing risk-averse optimization problems constrained by partial differential equations (PDEs), ...
A Locally Adapted Reduced Basis Method for Solving Risk-Averse ...
A Locally Adapted Reduced Basis Method for Solving Risk-Averse PDE-Constrained Optimization Problems · Wilkins Aquino, · Drew P. Kouri and · Zilong ...
An Interior-Point Approach for Solving Risk-Averse PDE ...
This has led to a growing interest in stochastic PDE-constrained optimization. 35. Whenever we are faced with making a decision under ...