The DAAD price of Cologne University of Applied Sciences (CUAS) goes this year to  Campus Gummersbach. The Iranian master student Samineh Bagheri from the Master programme "Automation & IT" is awarded with this price. Cordial congratulations!

Fachhochschule Köln

© Schmülgen/FH Köln


More information on this year's DAAD price are found in the official press release of CUAS (in German). Mrs. Samineh Bagheri currently writes her master thesis in the context of my research project MONREP and she works in MONREP as a student research assistant as well.

The 24th Workshop Computational Intelligence 2014, an annual conference held by Computational Intelligence (CI) Chapter of VDI-GMA (Gesellschaft für Mess- und Automatisierungstechnik) in Dortmund, has attributed the Young Author Award to Patrick Koch, PhD, scientific member of my research group at Campus Gummersbach. I am very happy for him and congratulate him cordially!

He got this award for the contribution

Constrained Optimization with a Limited Number of Function Evaluations

which he wrote as main author, conjointly with Samineh Bagheri, student in the master programme "Automation & IT", Prof. Dr. Thomas Bäck, Leiden University + divis intelligent solutions GmbH, and further colleagues from divis intelligent solutions GmbH.

The Young Author Award is an annual price since the year 2000 and is the for first time attributed to a member from the Cologne University of Applied Sciences and for the second time to an university of applied sciences in general.


The research leading to this contribution took place in the context of the ZIM research project MONREP. The theme of this work are optimization problems in high dimensions with many constraints and how they can be solved efficiently, i.e. with a low number of function evaluations.  This has a very realistic application background: In automotive industry it is desirable to minimize the weight of a car, but at the same time the car body has to meet all safety requirements. Each car design has to be tested carefully in very time-consuming simulations. This is the reason why only a low number of simulations (= function evaluations) is possible. The car designs are of course company secrets, but an equivalent benchmark with name MOPTA08 was released by the automotive industry and is one of the topics of our research. The figure above from the contribution by Patrick Koch shows that it is possible to achieve much better solutions with the help of a repair mechanism developed in MONREP. More details can be read in the preprint of the CI-workshop contribution.

MONREP was initiated by Prof. Thomas Bäck (divis GmbH) and Prof. Wolfgang Konen (Cologne University of Applied Sciences) and has a duration of 2 years (2014-2015). Dr. Patrick Koch works for MONREP as a senior researcher.

More details on MONREP in Pressemitteilung MONREP (PDF) (sorry, in German only!)

Mr. Markus Thill has won the first price in the 2012 OPITZ CONSULTING “Innovation in Informatics” contest. Many congratulations from the CIOP team!!


Mr. Thill’s thesis advanced the state of the art in reinforcement learning for complex board games, here Connect Four. Read more about his work on this page

The CIOP team is proud to announce that the latest version (V 0.9.0, February 2013) of the Tuned Data Mining in R (TDMR) package is now available for download on the Comprehensive R Archive Network (CRAN).

Downloading the new released version from this link. 


Title: Self-Adaptive Algorithms for Finding Robust Optima: Promises and Limitations
Time:   Fr., Oct, 26th, 2012, 11:00-11:45,
Place: Room 0.214


Many problems in engineering design deal with locating optimal parameter configurations for systems. Evolution strategies provide a robust framework for this. This talk deals with the question of how we can find optima that are robust to stochastic perturbations of the input variables and to noise on the output variables. A bifurcation-based classification of types of robust optima is provided, viewing the integration of robustness as a Weierstrass transformation. Based on dynamical systems analysis of evolution strategies the limits of self-adaptive schemes for controlling the sample size of self-adaptive robust evolution strategies are shown. Finally, some recently developed efficient archiving and modeling strategies for speeding up optimization with costly evaluations are highlighted.