On the robustness of a simple domain reduction scheme for simulation‐based optimization

By N. Stander, K. Craig. 2002

190 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computational Theory and Mathematics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/e2d151ac1a6f83de627dbd4b89ca0f6ea4bd9753

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Raphael T. Haftka

In Computational Theory and Mathematics

1. Anne-Laure Boulesteix
2. Tobias Pielok
3. Martin Binder
4. Michel Lang
5. Gerhard Venter
6. Jakob Richter
7. Marius Thomas Lindauer
8. Theresa Ullmann

In Statistics and Probability

1. Anne-Laure Boulesteix
2. Michel Lang
3. Gerhard Venter
4. Jakob Richter
5. Marius Thomas Lindauer
6. Bernd Bischl
7. Raphael T. Haftka
8. Gilles Louppe

Citations in the corpus

• Similarity measures for identifying material parameters from hysteresis loops using inverse analysis (2018, methodology): “First a metamodel (or surrogate) based optimization using the sequential domain reduction (SDRM) technique is run [41].”
• Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges (2021, background): “The package BayesianOptimization 17 can concentrate a domain around the current optimal values and adjust this domain dynamically (Stander & Craig, 2002).”