in progress


COSEAL - Configuration and Selection of Algorithms

The COSEAL research group is an international consortium of researchers from all over the world (e.g. Belgium, Canada, Ireland, Denmark and Germany) which addresses current challenges from Algorithm Selection, Algorithm Configuration and Machine Learning.

Project status in progress
Project time 01.02.2013- 01.01.2030
Keywords algorithm selection, configuration, machine learning

Joint research project: Identifying, verifying, and stopping concealed propaganda attacks via online media - Sub-Project: Coordination of simulation, identification, and defense against concealed propaganda attacks

This project addresses the identification and verification of (semi-)automated concealed propaganda in online media (e.g. in social networks) as an interdisciplinary approach.

Project status in progress
Project time 01.06.2016- 31.05.2019
Funding source Federal Ministry of Education and Research
Project number 16KIS0495K
Keywords Information Systems, Social Media, Propaganda, Public Opinion, Web

Instance-Based Algorithm Selection of Inexact TSP solvers

The Travelling Salesperson Problem (TSP) is arguably the most prominent NP-hard combinatorial optimisation problem. Given a set of n cities and pairwise distances between those, the objective in the TSP is to find the shortest round-trip or tour through all cities, i.e., a sequence in which every city is visited exactly once, the start and end cities are identical, and the total length of the tour is minimal. The Euclidean TSP has important applications, e.g., in the fabrication of printed circuit boards as well as in transportation and logistics. We aim at constructing an instance-based algorithm selection model in order to improve the current state-of-the-art solver.

Project status in progress
Project time 01.01.2017- 31.12.2018
Funding source German Academic Exchange Service
Project number 57314626
Keywords Algorithm Selection; TSP; automated algorithm selection; inexact solvers; Information Systems; Statistics; Canada

Architectures for Evolutionary Multi-Objective Algorithms to support User Expertise Integration

This project strives to analyze existing algorithm architectures and design new structures such that integration of expertise becomes seamlessly possible. Users should be free of the need to redesign or deeply understand the general algorithms structure.

Project status in progress
Project time since 01.09.2014
Keywords Computer Science, Algorithm Research, Application, Multi-Objective Optimization, Computational Intelligence

definitely finished


9th International Conference on Evolutionary Multi- Criterion Optimization, Münster 19. - 22.03.2017

EMO 2017 is the 9th International Conference on Evolutionary Multi- Criterion Optimization, aiming to continue the success of previous EMO conferences. We will bring together both the EMO and the multiple criteria decision making (MCDM) communities and moreover focus on solving real-world problems in government, business and industry. The classical EMO format will be supplemented by an EMO competition.

Project status definitely finished
Project time 19.03.2017- 22.03.2017
Funding source DFG - International Scientific Events
Project number TR 891/9-1
Keywords Evolutionary Multiobjective Optimization

Hybridization of indicator-based metaheuristics with modern local search methods in multiobjective optimization

The project realizes international expertise exchange between German and Mexican researchers in the context of hybrid evolutionary multi-objective optimization. A special focus lies on integrating local search into state-of-the-art meta-heuristics like SMS-EMOA and dP-EMOA.

Project status definitely finished
Project time 01.01.2014- 31.12.2015
Funding source German Academic Exchange Service
Project number 57065955
Keywords Computer Science, Evolutionary Multi-Objective Optimization, Local Search, Hybridization

Google Summer of Code 2015: Improving mlr's hyperparameter and tuning system for efficient model selection

This "Google Summer of Code 2015" project aims at enriching mlr's hyperparamter system with a-priori knowledge. The goal of the project is to make the hyperparameter configuration and tuning more flexible, efficient and convenient.

Project status definitely finished
Project time 27.04.2015- 31.08.2015
Keywords R, machine learning, algorithm configuration, parameter tuning, optimization

Addressing Current Challenges in Evolutionary Multi-Objective Optimization: Indicator-based Selection, Convergence and Applicability

This project aims to initiate and intensify bi-lateral collaboration of researchers from Brazil and Germany under the umbrella of current research topics in the domain of evolutionary multi-objective optimization.

Project status definitely finished
Project time 01.01.2014- 31.12.2014
Funding source DFG - Initiation of International Collaboration
Project number TR 891/7-1
Keywords Evolutionary Multi-Objective Optimization; Indicator-based Selection

Structural optimization of distributed energy supply systems - applied to chemical parks

The project aimed at setting up a method for structural optimization that enables the planning engineer to design a distributed energy supply system of near-optimal quality.

Project status definitely finished
Project time 01.06.2010- 31.08.2013
Keywords Optimization; Energy Supply Systems; MINLP; Multi-criterial Optimization