Eckart Zitzler received degrees from University of Dortmund in
Germany (diploma in computer science) and ETH Zurich in Switzerland
(doctor of technical sciences). Since 2003, he has been Assistant
Professor for Systems Optimization at the Computer Engineering and
Networks Laboratory at the Department of Information Technology and
Electrical Engineering of ETH Zurich, Switzerland. His research
focuses on bio-inspired computation, multiobjective optimization,
computational biology, and computer engineering applications.
Prof. Zitzler was General Co-Chairman of the first three international
conferences on evolutionary multi-criterion optimization (EMO 2001,
EMO 2003, and EMO 2005).

AG 1, AG 2, AG 3, AG 4, AG 5, SWS   Info

AG Audience

English

45 Minutes

Saarbrücken

Optimization problems involving multiple, possibly competing objective
functions such as cost vs. benefit are common in science and industry.
In such scenarios, it can be beneficial to explore the potential trade-offs
between the different criteria and to approximate the so-called
Pareto-optimal set, which contains those solutions that cannot be
improved in any criterion without degradation in another. To this end,
various generating methods have been proposed and in particular evolutionary
algorithms have been widely applied with the availability of sufficient
computing resources.

Despite the tremendous advances in the field of evolutionary multi-criterion
optimization - next year the fourth international conference on this subject
will take place - most of the work so far has focused on two or three
objectives. Various applications, though, require a multitude of
objectives to be considered, which poses new challenges and requires new
concepts and algorithms. This talk addresses two important aspects in this
context, namely preference-based search and dimensionality reduction, and
presents first, promising steps towards tackling high-dimensional problems.

Benjamin Doerr

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