Category Archives: Sequential Parameter Optimization

Prof. Bartz-Beielstein invited as a COST action trainer at Sorbonne Universités


Prof. Bartz-Beielstein was invited as a COST Action trainer to give a lecture at  Sorbonne Universités – Université Pierre et Marie Curie (UPMC).
The COST Action CA15140 “Improving Applicability of Nature-Inspired Optimisation by Joining Theory and Practice (ImAppNIO)” organized a training school on the theme of the COST Action: bridging the gap between theory and practice and making nature-inspired search and optimization heuristics (like for example evolutionary algorithms) more applicable. Continue reading

Free Online-Version: Metamodel-based optimization of hot rolling processes in the metal industry


The article “Metamodel-based optimization of hot rolling processes in the metal industry” is published in The International Journal of Advanced Manufacturing. As part of the Springer Nature SharedIt initiative, a publicly full-text view-only version of this paper is available here.

The abstract reads as follows: Continue reading

Successful Presentations @useR!2017 Brussels

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Last week the useR! 2017 conference took place in Brussels, Belgium. The annual useR! conference is the main meeting of the international R user and developer community. Over 1000 participants came to listen to a broad spectrum of talks ranging from technical and R-related computing issues to general statistical topics of current interest .

Here you find some impressions from the conference: Pictures

The SPOTSeven team gave two presentations:

Here you can find the slides:

The talks enjoyed great participation and resulted in lots of interesting discussions afterwards.

Last chance: Free access to article about Model-based Methods #optimization

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

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