Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/66821
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Type: Conference paper
Title: Analyzing Hypervolume Indicator Based Algorithms
Author: Brockhoff, D.
Friedrich, T.
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.651-660
Publisher: Springer
Publisher Place: Berlin
Issue Date: 2008
Series/Report no.: Lecture Notes in Computer Science
ISBN: 3540876995
9783540876991
ISSN: 0302-9743
1611-3349
Conference Name: Conference on Parallel Problem Solving from Nature (10th : 2008 : Dortmund, Germany)
Statement of
Responsibility: 
Dimo Brockhoff, Tobias Friedrich, and Frank Neumann
Abstract: Indicator-based methods to tackle multiobjective problems have become popular recently, mainly because they allow to incorporate user preferences into the search explicitly. Multiobjective Evolutionary Algorithms (MOEAs) using the hypervolume indicator in particular showed better performance than classical MOEAs in experimental comparisons. In this paper, the use of indicatorbased MOEAs is investigated for the first time from a theoretical point of view. We carry out running time analyses for an evolutionary algorithm with a (μ+1)-selection scheme based on the hypervolume indicator as it is used in most of the recently proposed MOEAs. Our analyses point out two important aspects of the search process. First, we examine how such algorithms can approach the Pareto front. Later on, we point out how they can achieve a good approximation for an exponentially large Pareto front.
Description: Also published as a journal article: Lecture notes in computer science, 2008; 5199:651-660
Rights: © Springer-Verlag Berlin Heidelberg 2008
RMID: 0020107065
DOI: 10.1007/978-3-540-87700-4_65
Published version: https://doi.org/10.1007/978-3-540-87700-4
Appears in Collections:Computer Science publications

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