Analyzing Hypervolume Indicator Based Algorithms
Date
2008
Authors
Brockhoff, D.
Friedrich, T.
Neumann, F.
Editors
Rudolph, G.
Jansen, T.
Lucas, S.
Poloni, C.
Beume, N.
Jansen, T.
Lucas, S.
Poloni, C.
Beume, N.
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
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
Statement of Responsibility
Dimo Brockhoff, Tobias Friedrich, and Frank Neumann
Conference Name
Conference on Parallel Problem Solving from Nature (10th : 2008 : Dortmund, Germany)
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.
School/Discipline
Dissertation Note
Provenance
Description
Also published as a journal article: Lecture notes in computer science, 2008; 5199:651-660
Access Status
Rights
© Springer-Verlag Berlin Heidelberg 2008