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  Convergence of Hypervolume-Based Archiving Algorithms I: Effectiveness

Bringmann, K., & Friedrich, T. (2011). Convergence of Hypervolume-Based Archiving Algorithms I: Effectiveness. In N. Krasnogor, & P. L. Lanzim (Eds.), GECCO 2011 (pp. 745-752). New York, NY: ACM. doi:10.1145/2001576.2001678.

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 Urheber:
Bringmann, Karl1, Autor           
Friedrich, Tobias1, Autor           
Affiliations:
1Algorithms and Complexity, MPI for Informatics, Max Planck Society, ou_24019              

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Schlagwörter: -
 Zusammenfassung: The core of hypervolume-based multi-objective evolutionary algorithms is an archiving algorithm which performs the environmental selection. A (μ+λ)- archiving algorithm defines how to choose μ children from μ parents and λ offspring together. We study theoretically (μ+λ)-archiving algorithms which never decrease the hypervolume from one generation to the next. Zitzler, Thiele, and Bader (IEEE Trans. Evolutionary Computation, 14:58-79, 2010) proved that all (μ+1)-archiving algorithms are ineffective, which means there is an initial population such that independent of the used reproduction rule, a set with maximum hypervolume cannot be reached. We extend this and prove that for λ<μ all archiving algorithms are ineffective. On the other hand, locally optimal algorithms, which maximize the hypervolume in each step, are effective for λ=μ and can always find a population with hypervolume at least half the optimum for λ<μ. We also prove that there is no hypervolume-based archiving algorithm which can always find a population with hypervolume greater than 1/(1+0.1338(1/λ-1/μ)) times the optimum.

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Sprache(n): eng - English
 Datum: 20112011
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: eDoc: 618721
DOI: 10.1145/2001576.2001678
URI: http://doi.acm.org/10.1145/2001576.2001678
Anderer: Local-ID: C1256428004B93B8-3DED5E5BC5A335DEC1257984004D9BA0-BringmannF2011
 Art des Abschluß: -

Veranstaltung

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Titel: 2011 Genetic and Evolutionary Computation Conference
Veranstaltungsort: Dublin, Ireland
Start-/Enddatum: 2011-07-12 - 2011-07-16

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Titel: GECCO 2011
  Untertitel : Genetic and Evolutionary Computation Conference
Genre der Quelle: Konferenzband
 Urheber:
Krasnogor, Natalio1, Herausgeber
Lanzim, Pier Luca1, Herausgeber
Affiliations:
1 External Organizations, ou_persistent22            
Ort, Verlag, Ausgabe: New York, NY : ACM
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 745 - 752 Identifikator: ISBN: 978-1-4503-0557-0