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What and Who
Title:Multi-Objective Evolutionary Algorithms for Bioinformatics
Speaker:Luis Enrique Ramirez Chavez
coming from:Max-Planck-Institut für Informatik
Speakers Bio:
Event Type:IMPRS Research Seminar
Visibility:D1, D2, D3, D4, D5, SWS, RG1, MMCI
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Level:AG Audience
Date, Time and Location
Date:Monday, 15 June 2015
Duration:20 Minutes
Building:E1 4
In engineering and scientific applications, there exist problems that
involve the simultaneous optimization of several objectives. Usually, such
objectives are conflicting such that no single solution is simultaneously
optimal with respect to all objectives. These types of problems are known
as Multi-objective Optimization Problems (MOPs).

For these more complex optimization problems, the use of meta-heuristics
is fully justified. Multi-Objective Evolutionary Algorithms (MOEAs) are
meta-heuristics which, in recent years, have become very popular because
of their conceptual simplicity and efficiency in these types of problems.
For their nature (based on a population), MOEAs allow to generate multiple
Pareto optimal solutions in a single run. Therefore, nowadays, MOEAs
constitute one of the most successful approaches for solving MOPs.

Numerous of problems encountered in bioinformatics and computational
biology can be formulated as optimization problems and, thus, lend
themselves to the application of powerful heuristic search techniques.
Recently, in biology, Multi-objective optimization has been shown to have
significant benefits compared to single-objective approaches, e.g., in
classification, system optimization and inverse problems.

In this talk I will present some of the MOEAs approaches that have been
used to solve different kind of bioinformatics problems.
Name(s):Andrea Ruffing
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Created by:Andrea Ruffing/AG5/MPII/DE, 06/12/2015 03:27 PMLast modified by:Uwe Brahm/MPII/DE, 11/24/2016 04:13 PM
  • Andrea Ruffing, 06/12/2015 03:30 PM -- Created document.