Multi-Modal Optimization with Evolutionary Algorithms: It concerns research on evolutionary algorithms for multi-modal optimization, preparing a contemporary state-of-the-art, comparing a number of popular approaches on some benchmark data as well as extending selected existing approaches for increasing their efficiency on selected application domains. For more details please contact Piotr Lipinski.
Evolutionary Algorithms for Multi-Dimensional Multi-Objective Optimization: It concerns research on evolutionary algorithms for multi-objective optimization problems with a large number of objective functions as well as a large number of dimensions of the search space. It assumes preparing a contemporary state-of-the-art, comparing a number of popular approaches on some benchmark data, including such evolutionary algorithms as NSGA-II, SPEA2 and MOEA/D, as well as extending selected existing approaches for increasing their efficiency on selected application domains. For more details please contact Piotr Lipinski.
Data Mining Techniques for Load Balancing and Control in Popular Issue Trackers: It concerns applying selected data mining techniques to enrich popular issue tracker software (e.g. JIRA) with the aim of improving load balancing and control. It assumes designing and developing some plugins for popular issue tracker and evaluating the efficiency of the proposed improvements on some benchmark data. For more details please contact Piotr Lipinski.
CIRG, Computational Intelligence Research Group, Institute of Computer Science, University of Wroclaw, Poland
