Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/66762
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Type: Conference paper
Title: Benefits and drawbacks for the use of ε-dominance in evolutionary multi-objective optimization
Other Titles: Benefits and drawbacks for the use of epsilon-dominance in evolutionary multi-objective optimization
Author: Horoba, C.
Neumann, F.
Citation: GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation / M. Keijzer (ed.), pp.641-680
Publisher: ACM New York
Publisher Place: New York
Issue Date: 2008
ISBN: 9781605581309
Conference Name: Genetic and Evolutionary Computation Conference (10th : 2008 : Atlanta, Georgia)
Editor: Ryan, C.
Keijzer, M.
Statement of
Responsibility: 
Christian Horoba, Frank Neumann
Abstract: Using diversity mechanisms in evolutionary algorithms for multi-objective optimization problems is considered as an important issue for the design of successful algorithms. This is in particular the case for problems where the number of non-dominated feasible objective vectors is exponential with respect to the problem size. In this case the goal is to compute a good approximation of the Pareto front. We investigate how this goal can be achieved by using the diversity mechanism of ε-dominance and point out where this concept is provably helpful to obtain a good approximation of an exponentially large Pareto front in expected polynomial time. Afterwards, we consider the drawbacks of this approach and point out situations where the use of ε-dominance slows down the optimization process significantly. Copyright 2008 ACM.
Keywords: Multi-objective optimization
Running time analysis
Rights: Copyright 2008 ACM
DOI: 10.1145/1389095.1389224
Description (link): http://www.sigevo.org/gecco-2008/
Published version: http://dx.doi.org/10.1145/1389095.1389224
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Computer Science publications

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