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Neuigkeiten aus der Forschung
 Die Sequential Parameter Optimization Technology (SPOT) stellt ein Vorgehensmodell zur Simulation, Optimierung und Analyse komplexer Prozesse dar. Neuigkeiten zur SPOT finden Sie hier (GooglePlus).
Research interests and cooperations
 Thomas Bartz-Beielstein is Professor of Applied Mathematics at Cologne University of Applied Sciences. His interests include Design and Analysis of Experiments, Stochastic Optimization, and Computational Intelligence.

He is member of the research group COSA - Computational Services in Automation.

Prof. Bartz-Beielstein is (in company with Prof. Konen) head of the research center Computational Intelligence, Optimization and Data Mining (CIOP).

He is head of the research projects FIWA (Methoden der Computational Intelligence für Vorhersagemodelle in der Finanz- und Wasserwirtschaft), MCIOP (Mehrkriterielle CI-basierte Optimierungsverfahren für den industriellen Einsatz) und CIMO (Computational Intelligence basierte Mehrzieloptimierungsverfahren).
In seinem Team arbeiten momentan zwei Postdoktoranden, vier Doktoranden, und zwei Masterstudenten sowie mehrere studentische Hilfskräfte.

Sequential Parameter Optimization (SPO)

 The sequential parameter optimization toolbox SPOT was developed over the last years by Thomas Bartz-Beielstein, Christian Lasarczyk, and Mike Preuss. The main purpose of SPOT is to determine improved parameter settings for optimization algorithms to analyze and understand their performance.
SPOT was successfully applied to numerous optimization algorithms, especially in the field of evolutionary computation, i.e., evolution strategies, particle swarm optimization, algorithmic chemistries etc. in the following domains:
  • machine engineering: design of mold temperature control
  • aerospace industry: airfoil design optimization
  • simulation and optimization: elevator group control
  • technical thermodynamics: non sharp separation
  • economy: agri-environmental policy-switchings
  • algorithm engineering: graph drawing
  • statistics: selection under uncertainty (optimal computational budget allocation) for PSO
  • evolution strategies: threshold selection and step-size adaptation
  • genetic chromodynamics
  • computational intelligence: algorithmic chemistry
  • particle swarm optimization: analysis and application
  • numerics: comparison and analysis of classical and modern optimization algorithms
  • vehicle routing and door-assignment problems
  • bioinformatics
  • storm water management
  • differential and integral equations
  • time series analysis
An R version of this toolbox for interactive and automatic optimization of algorithms can be downloaded from CRAN.

Join the group Sequential Parameter Optimization Toolbox at ResearchGATE: Join the group Sequential Parameter Optimization Toolbox at ResearchGATE



pfeil_grau Downloads
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SPOT related papers and manuals
icon_datei SPOT Manual (1004457Bytes)
icon_datei Spocec (696992Bytes)
icon_datei Spotannotatedbib (307140Bytes)

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SPOT
Sequential Parameter Optimization Technology (SPOT)
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© 2011 FH Köln blank Impressum blank Haftungshinweis blank Druckversion bearbeitet von: Bartz-Beielstein blank geändert am: 30.11.2011