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On July 25, 2017, I gave my research talk on Automating Scientific Research in Optimization at the Simulation and Optimal Processes Group of  Prof. Dr. Pu Li [李浦]. at the Institute for Automation and Systems EngineeringDepartment of Computer Science and Automation at the Technische Universität Ilmenau (TU Ilmenau) in Ilmenau, Germany.

The group contributes both fundamental as well as applied research. In terms of the former, they focus on the dynamic optimization of large systems, optimization under uncertainties, real-time optimization, and non-linear model-driven control. They apply their researcher to energy systems, autonomous driving, water management, systems biology, and process engineering. What is fascinating about this research group is that they combine several research fields of applied optimization which will have a huge future: The work on energy and water network optimization is directly relevant to the immediate challenges our society faces in the next few decades. Global warming causes problems with water supply and trying to reduce global warming means that we need to change and improve our way of obtaining, transmitting, and using (renewable) energy. Autonomous driving, on the other hand, is one of the trends which will change transportation and traffic significantly. Trying to optimize any complex real-world system, be it a energy or water network, the production lines in a factory or the logistics of an enterprise cannot be done efficiently without dealing with uncertainties since we make plans for the future but can never know the future exactly. Optimization of complex systems or of engineering designs often requires simulations.

I am thankful for the chance to present at this strong research group and to Prof. Li for arranging my talk. It definitely was a very nice meeting.

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On July 24, 2017, I gave a research talk at the Computational Intelligence Group of the Faculty of Applied Computer‐ and Bio­sciences, University of Applied Sciences Mittweida (HSMW, Hochschule Mittweida). During these days, the group hosts the 9th Mittweida Workshop on Computational Intelligence (MiWoCI) and Prof. Dr. Thomas Villmann, the group head and one of the two workshop organizer, kindly provided me a time slot at the workshop for my presentation*.

The workshop itself had a very international line up of both research and industry talks with researchers from the University of Groningen (The Netherlands), the Cluster of Excellence Cognitive Interaction Technology (CITEC) of the Bielefeld University (Germany), Porsche, the Honda Research Institute (Germany), the University of Applied Sciences Würzburg-Schweinfurt (FHWS, Germany), the  Dresden (HTW, Germany) and of course the Computational Intelligence Group itself. I really regret that I could only attend the workshop at its first day. The talks that I could attend were all very interesting and underlined the excellent contributions that Computational Intelligence and Operations Research can make to the industry.

Visiting Mittweida also allowed me to get to know the Computational Intelligence Group and their research, which is mainly focused on secure classification of high-dimensional data and BigData with machine learning methods. They work on self-organizing maps, semi-supervised learning, fuzzy classification and clustering, information theoretic learning, non-standard metrics in vector quantization, prototype-based classification learning vector quantization (LVQ), Evolutionary Algorithms, and high-dimensional data analysis for, e.g., mass spectrometry data analysis in medicine as well as class visualization and projection. Like our institute, they work both on theoretical questions and practical applications.

Presenting and discussing our work in this environment of a workshop and an application-oriented research group, both on exactly our topic area, was a very pleasant experience and I want to than Prof. Villmann again for making this possible.

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On July 21, 2017, I have given the research talk "Automating Scientific Research in Optimization" at the Artificial Intelligence Group of the Faculty of Computer Science, Chemnitz University of Technology [Technische Universität Chemnitz] in Chemnitz, Germany. The host of the talk was Dr. Julien Vitay who welcomed me also in the name of Prof. Dr. Fred Hamker. I was particularly happy to come back here and present our work, as the TU Chemnitz is my old alma mater, the AI Group has a wide variety of very interesting projects, and I even presented in the very same room where I defended my Master's thesis work more than twelve years ago.

The group is renowned for its research on model-driven approaches for exploring visual perception and cognition, having contributed significantly to the topics of object recognition, conscious perception, attention, cognitive control of visual perception, and space perception. It also investigates novel deep learning technologies. Besides contribution much to fundamental research, the group also provides the open source software Artificial Neural Networks architect (ANNarchy), a parallel and hybrid simulator for distributed rate-coded or spiking neural networks written mainly in C++ and parallelized using openMP or CUDA. The group is furthermore associated with the Bernstein Center for Computational Neuroscience Berlin (bccn).

Like my talk yesterday at the Friedrich Schiller University in Jena, the talk was received with broad interest. I am very thankful to Dr. Vitay and Prof. Hamker for publicizing this presentation. The comprehensive thought exchanges before and after talk were also truly inspiring.

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On July 20, 2017, I have given the research talk "Automating Scientific Research in Optimization" at the Mathematical Optimization group of Prof. Dr. Ingo Althöfer and Prof. Dr. Andreas Löhne at the Department of Mathematics of the Faculty of Mathematics and Computer Science of the Friedrich Schiller University Jena (FSU, Friedrich-Schiller-Universität Jena) in Jena, Germany.

The group of Prof. Löhne is well-known for their research on vector optimization and multi-objective linear programming. They provide an open source software, Bensolve, for multi-objective / vector linear programming written in C as well as the Multi-Objective Problem LIBrary (MOPLIB) of instances of multi-objective linear, multi-objective (mixed) integer and vector linear programs. The visit to the Mathematical Optimization posed a very interesting chance for discussion, as linear programming and metaheuristics (our field) are two entirely different approaches to optimization, having different advantages and disadvantages.

The talk went well and I am very thankful to Prof. Löhne for the hospitality he showed to me. For me, it is always very inspiring to learn about a topic area with which I am not very familiar yet. The vector optimization of Prof. Löhne is such a field, and I think the exchange of thoughts that we had regarding both of our research areas (both belonging to the domain of optimization) was very inspiring.

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I am currently attending the Genetic and Evolutionary Computation Conference (GECCO'17), taking place from July 15 to 19, 2017 in Berlin, Germany. GECCO is the primary event in the world on Evolutionary Computation. I have attended it before in 2008, 2010, 2012, and 2016 and always enjoyed this conference very much. Our group has two papers there this year, namely:

  • Weichen Liu, Thomas Weise, Yuezhong Wu, and Qi Qi. Combining Two Local Searches with Crossover: An Efficient Hybrid Algorithm for the Traveling Salesman Problem. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'17), July 15-19, 2017, Berlin, Germany, New York, NY, USA: ACM Press, pages 298-305, ISBN: 978-1-4503-4920-8.
    doi:10.1145/3071178.3071201 / paperslides
  • Qi Qi, Thomas Weise, and Bin Li. Modeling Optimization Algorithm Runtime Behavior and its Applications. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'17) Companion, July 15-19, 2017, Berlin, Germany, New York, NY, USA: ACM Press, pages 115-116, ISBN: 978-1-4503-4939-0.
    doi:10.1145/3067695.3076042 / paperposter

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