Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/66820
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Type: Conference paper
Title: Runtime analyses for using fairness in evolutionary multi-objective optimization
Author: Friedrich, T.
Horoba, C.
Neumann, F.
Citation: Parallel problem solving from nature - PPSN X : 10th International Conference, Dortmund, Germany, September 13-17, 2008 ; proceedings / Günter Rudolph ... [et al.] (eds.), pp.671-680
Publisher: Springer
Publisher Place: Berlin
Issue Date: 2008
Series/Report no.: Lecture Notes in Computer Science; 5199
ISBN: 3540876995
9783540876991
ISSN: 0302-9743
1611-3349
Conference Name: Conference on Parallel Problem Solving from Nature (10th : 2008 : Dortmund, Germany)
Statement of
Responsibility: 
Tobias Friedrich, Christian Horoba, and Frank Neumann
Abstract: It is widely assumed that evolutionary algorithms for multi-objective optimization problems should use certain mechanisms to achieve a good spread over the Pareto front. In this paper, we examine such mechanisms from a theoretical point of view and analyze simple algorithms incorporating the concept of fairness introduced by Laumanns et al. [7]. This mechanism tries to balance the number of offspring of all individuals in the current population. We rigorously analyze the runtime behavior of different fairness mechanisms and present showcase examples to point out situations where the right mechanism can speed up the optimization process significantly.
Description: Also published as a journal article: Lecture notes in computer science, 2008; 5199:671-680
Rights: © Springer-Verlag Berlin Heidelberg 2008
RMID: 0020107060
DOI: 10.1007/978-3-540-87700-4_67
Published version: https://doi.org/10.1007/978-3-540-87700-4
Appears in Collections:Computer Science publications

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