Robust optimization using computer experiments
From MaRDI portal
Publication:932202
DOI10.1016/j.ejor.2007.03.048zbMath1160.65321OpenAlexW2128609443MaRDI QIDQ932202
Erwin Stinstra, Dick den Hertog
Publication date: 10 July 2008
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://pure.uvt.nl/ws/files/774854/90.pdf
Applications of statistics in engineering and industry; control charts (62P30) Numerical mathematical programming methods (65K05)
Related Items (11)
Expected improvement based infill sampling for global robust optimization of constrained problems ⋮ A robust desirability function method for multi-response surface optimization considering model uncertainty ⋮ Decision uncertainty in multiobjective optimization ⋮ Diametrical risk minimization: theory and computations ⋮ Hidden conic quadratic representation of some nonconvex quadratic optimization problems ⋮ A new loss function for multi-response optimization with model parameter uncertainty and implementation errors ⋮ The dynamic Black-Litterman approach to asset allocation ⋮ Robust Optimization in Simulation: Taguchi and Krige Combined ⋮ 10 Kriging: methods and applications ⋮ Portfolio selection under distributional uncertainty: a relative robust CVaR approach ⋮ Fabrication-Adaptive Optimization with an Application to Photonic Crystal Design
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Robust design of structures using optimization methods
- Multipoint Taylor formulae
- Applications of convex optimization in signal processing and digital communication
- Design and analysis of computer experiments. With comments and a rejoinder by the authors
- Optimizing color picture tubes by high-cost nonlinear programming
- Robust optimization-methodology and applications
- A taxonomy of global optimization methods based on response surfaces
- On robust solutions to linear least squares problems affected by data uncertainty and implementation errors with application to stochastic signal modeling
- Automatic Differentiation in Robust Optimization
- Implementation of interior point methods for mixed semidefinite and second order cone optimization problems
- On convex quadratic approximation
- Multivariate Nonnegative Quadratic Mappings
- Robust Solutions to a General Class of Approximation Problems
- Application-driven sequential designs for simulation experiments: Kriging metamodelling
This page was built for publication: Robust optimization using computer experiments
