- Written by: Thomas Weise
Today, we released the new version 0.8.9 of our optimizationBenchmarking.org software framework for automating significant parts of the research in the fields of optimization, machine learning, and operations research. This new version comes much closer to our goal to reduce the workload of researchers and practitioners during the development of algorithms to allow them to spend more time on thinking.
Besides all the functionality offered by the previous releases, it introduces a new process for obtaining high-level conclusions about problem hardness and algorithm behaviors. This process takes the raw data from experiments together with meta-information about algorithm setups and problem instances as input. It applies a sequence of machine learning technologies, namely curve fitting, clustering, and classification, to find which features make a problem instance hard and which algorithm setup parameters cause which algorithm behavior. We just submitted an article about this new process for review.
Our software provides a set of very general tools for algorithm performance analysis (e.g., plotting runtime/quality and ECDF charts) as well as our new process. Since it takes data in form of text files, it can analyze the results of any optimization algorithm implemented in any programming language applied to any optimization problem. It produces human-readable reports either in form of LaTeX/PDF documents or as XHTML.
The software provides a user-friendly, web-based GUI which runs either on your local machine or a server in your lab comes. The software comes in three flavors:
- as Java executable, requiring that several tools are installed (Java, R with several packages, a LaTeX system installation),
- as Docker image, which only requires an installation of Docker. It can be started directly under Linux, Windows, and Mac OS with the single command
docker run -t -i -p 9999:8080/tcp optimizationbenchmarking/evaluator-guiand then is used by browsing to http://localhost:9999. (At first start, the image is downloaded), and - as command line program without GUI for integration in other software environments (with the same installation requirements as the GUI),
- Written by: Thomas Weise
The Institute of Applied Optimization and the Faculty of Computer Science and Technology of the Hefei University welcome Ms. Tatiana Vorontsova [Татьяна Воронцова], an exchange student from Nizhni Novgorod [Ни́жний Но́вгород] in the Russian Federation.
Ms. Vorontsova will join our university for the Summer Semester 2017. She will study several computer science courses, including the course "Object-Oriented Programming with Java" newly designed by Prof. Dr. Thomas Weise. Additionally, she will of course also study the Chinese culture and language.
We wish Ms. Vorontsova a nice stay in Hefei and at our university.