An efficient class of direct search surrogate methods for solving expensive optimization problems with CPU-time-related functions
DOI10.1007/s00158-011-0658-3zbMath1274.74006OpenAlexW2007249905MaRDI QIDQ381689
Mark A. Abramson, Raymond jun. Magallanez, Matthew J. Sottile, John E. jun. Dennis, Thomas J. Asaki
Publication date: 15 November 2013
Published in: Structural and Multidisciplinary Optimization (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/1911/102088
pattern searchderivative-free optimizationimage registrationKrigingblack box optimization\texttt{DACE}\texttt{MATLAB}\texttt{NOMADm}mesh adaptive direct search (MADS)surrogate optimization
Applications of mathematical programming (90C90) Optimization of other properties in solid mechanics (74P10) Software, source code, etc. for problems pertaining to mechanics of deformable solids (74-04)
Related Items
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Kriging metamodeling in simulation: a review
- Interpolation of spatial data. Some theory for kriging
- Curvature based image registration
- Design and analysis of computer experiments. With comments and a rejoinder by the authors
- On the Convergence of Pattern Search Algorithms
- Condition Estimates
- Convergence of Mesh Adaptive Direct Search to Second‐Order Stationary Points
- OrthoMADS: A Deterministic MADS Instance with Orthogonal Directions
- Large Sample Properties of Simulations Using Latin Hypercube Sampling
- Orthogonal Array-Based Latin Hypercubes
- Numerical Simulation in Fluid Dynamics
- Analysis of Generalized Pattern Searches
- A Block Algorithm for Matrix 1-Norm Estimation, with an Application to 1-Norm Pseudospectra
- Pattern Search Methods for Linearly Constrained Minimization
- A Pattern Search Filter Method for Nonlinear Programming without Derivatives
- Pattern Search Algorithms for Bound Constrained Minimization
- A Globally Convergent Augmented Lagrangian Pattern Search Algorithm for Optimization with General Constraints and Simple Bounds
- Multi-Objective Optimization Using Surrogates
- Mesh Adaptive Direct Search Algorithms for Constrained Optimization
- Frame based methods for unconstrained optimization