Category Archives: Surrogate Models

Interested in #ModelBased Methods for #Optimization? #SPOT2

If you are interested in “Model-based Methods for Continuous and Discrete Global Optimization“, you can freely access the article until April 11, 2017:
https://authors.elsevier.com/a/1Ub295aecSVmv2
The SPO Toolbox was used for performing the experiments described in this article. The Sequential Parameter Optimization Toolbox 2.0.1 is a major update of the SPOT R package. It provides a set of tools for model based optimization and tuning of algorithms. It includes surrogate models, optimizers and design of experiment approaches. The main interface is spot, which uses sequentially updated surrogate models for the purpose of efficient optimization. The main goal is to ease the burden of objective function evaluations, when a single evaluation requires a significant amount of resources. See: https://CRAN.R-project.org/package=SPOT

Sequential Parameter #Optimization Toolbox SPOT 2.0.1 on CRAN #rstats

SPOT: Sequential Parameter Optimization Toolbox 2.0.1

This is a major update of the R package. The SPO toolbox provides a set of tools for model based optimization and tuning of algorithms. It includes surrogate models, optimizers and design of experiment approaches. The main interface is spot, which uses sequentially updated surrogate models for the purpose of efficient optimization. The main goal is to ease the burden of objective function evaluations, when a single evaluation requires a significant amount of resources. See: https://CRAN.R-project.org/package=SPOT

@UTOPIAE_network @TH_Koeln: Uncertainty Treatment and OPtimisation In Aerospace Engineering

Mit “UTOPIAE – Uncertainty Treatment and OPtimisation In Aerospace Engineering” beteiligt sich die TH Köln zum vierten Mal an einem von der EU geförderten Marie-Curie-Innovations-Ausbildungsprogramm. Mit rund 3.9 Millionen Euro Fördersumme forschen europaweit 15 Doktorandinnen und Doktoranden interdisziplinär an der Optimierung der computergenerierten Konstruktion von Luft- und Raumfahrtzeugen.
Koordiniert von der Strathclyde University in Schottland arbeiten insgesamt 15 Hochschulen, Forschungseinrichtungen und Firmen in Großbritannien, Italien, Belgien, Frankreich und den USA zusammen. Darunter die Stanford University, Airbus Operations GmbH und die Deutsche Luft- und Raumfahrt. Die TH Köln übernimmt dabei Aufgabenbereiche aus der Mathematik und Informatik unter der Leitung der Professoren Dr. Thomas Bartz-Beielstein und Dr. Boris Naujoks von der Fakultät für Informatik und Ingenieurwissenschaften.

Den vollständigen Text der Pressemitteilung finden Sie unter https://www.th-koeln.de/hochschule/utopiae–uncertainty-treatment-and-optimisation-in-aerospace-engineering_41808.php

Click and Read! Free Access: Continuous and Discrete Global #Surrogate #Optimization

http://dx.doi.org/10.1016/j.asoc.2017.01.039Just click and read! Everybody can use the following personal article link, which will provide free access to the article “Model-based methods for continuous and discrete global optimization” (Thomas Bartz-Beielstein, Martin Zaefferer), and is valid for 50 days, until April 11, 2017:
https://authors.elsevier.com/a/1Ub295aecSVmv2

Here are some highlights:

  • Up-to-date survey and comprehensive taxonomy of surrogate model based optimization algorithms.
  • Covers continuous and discrete/combinatorial search spaces.
  • Presents six strategies for dealing with discrete data structures.
  • New strategy for model selection and combination in surrogate model-based optimization.
  • Outlook on important challenges (model selection, dimensionality, benchmarks, definiteness) and research directions.

Continue reading