Category Archives: Multi Objective Optimization

CFP: Parallelization and surrogate modelling in multi objective optimization

Call for papers: Special Session “Parallelization and surrogate modelling in multi objective optimization” at META 2016, the 6th International Conference on Metaheuristics and Nature Inspired Computing.
27-31 Oct 2016, Marrakech, Morocco.
Paper submission deadline 6 May 2016. More: http://meta2016.sciencesconf.org/

EU-Projekt: Mehr als 1 Million EUR Fördermittel

Im Rahmen des EU-Programms für Forschung und Innovation „Horizon 2020“ gibt es die Säule „Verbreitung von Exzellenz und Ausweitung der Beteiligung“ (http://www.eubuero.de/ausweitung.htm), der verschiedene Förderlinien zugeordnet sind. In einer dieser Förderlinien, „Twinning: Partnerschaften von Forschungseinrichtungen“ hat Prof. Boris Naujoks in Zusammenarbeit mit Prof. Thomas Bartz-Beielstein und weiteren Partnern aus Frankreich und Slowenien  erfolgreich eine Projektförderung eingeworben. Continue reading

Impressions from the CFD Workshop

Here are some photos that illustrate the inspiring atmosphere during the first CFD Workshop at Cologne University of Applied Sciences, Faculty of Computer Science and Engineering Science in Gummersbach. The workshop was organized by SPOTSeven in cooperation with Steinmüller Engineering GmbH and TU Clausthal – Institute for Energy Process Engineering and Fuel Technology.

 

CFD Workshop am Campus Gummersbach der FH Köln

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Der erste Computational Fluid Dynamics Workshop, der von der SPOTSeven Forschungsgruppe in Zusammenarbeit mit der Steinmüller Engineering GmbH und der TU Clausthal organisiert wurde, fand heute in Gummersbach statt. Das Programm beinhaltete die folgenden Vorträge: Continue reading

Tutorial Slides Freely Available: How to create meaningful and generalizable results

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Slides from the GECCO’13 tutorial “How to create meaningful and generalizable results” are freely available on SPOTSeven’s publication page.

Computational Intelligence (CI) methods have gained importance in several real-world domains such as process optimization, system identification, data mining, or statistical quality control. Tools, which determine the applicability of CI methods in these application domains in an objective manner, are lacking. Statistics provide methods for comparing algorithms on certain data sets. In the past, several test suites were presented and considered as state-of-the-art. However, there are several drawbacks of these test suites, namely:

  • problem instances are somehow artificial and have no direct link to real-world settings;
  • since there is a fixed number of test instances, algorithms can be fitted or tuned to this specific and very limited set of test functions. As a consequence, studies (benchmarks) provide insight into how these algorithms perform on this specific set of test instances, but no insight is gained in how they perform in general;
  • statistical tools for comparing several algorithms on different test problem instances are relatively complex and results are not easy to analyze.

In this tutorial, a methodology to overcome these difficulties is presented. It is based on standard ideas from statistics: analysis of variance and its extension to mixed models, see, e.g. [Chia10a]. This tutorial combines essential ideas from two approaches: problem generation and statistical analysis of computer experiments. This framework extends ideas presented in [Bart11g].The generalization of results from multi-objective optimization problems will also be addressed.

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Evolutionäre Optimierung aus Sicht der Praxis

Dr.-Ing. Jörn Mehnen, Cranfield University, UK, besuchte das SPOTSeven Team in der letzten Woche, um gemeinsame Forschungsprojekte abzustimmen. Zudem organisieren Dr. Mehnen und Prof. Bartz-Beielstein die renommierte Vortragsreihe “Evolutionary Computation in Practice“, die jährlich im Rahmen der Konferenz GECCO stattfindet. Dr. Mehnen hielt einen Vortrag mit dem Titel “Evolutionäre Optimierung aus der Sicht der Praxis” im SPOTSeven Seminar.  Continue reading