Autor(en): | Giel, Oliver Lehre, Per Kristian |
Titel: | On the effect of populations in evolutionary multi-objective optimization |
Sprache (ISO): | en |
Zusammenfassung: | Multi-objective evolutionary algorithms (MOEAs) have become increasingly popular as multi-objective problem solving techniques. Most studies of MOEAs are empirical. Only recently, a few theoretical results have appeared. It is acknowledged that more theoretical research is needed. An important open problem is to understand the role of populations in MOEAs. We present a simple bi-objective problem which emphasizes when populations are needed. Rigorous runtime analysis point out an exponential runtime gap between a population-based algorithm (SEMO) and several single individual-based algorithms on this problem. This means that among the algorithms considered, only the populationbased MOEA is successful and all other algorithms fail. |
URI: | http://hdl.handle.net/2003/24343 http://dx.doi.org/10.17877/DE290R-9000 |
Erscheinungsdatum: | 2007-06-04T16:20:03Z |
Enthalten in den Sammlungen: | Sonderforschungsbereich (SFB) 531 |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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20206.pdf | DNB | 301.29 kB | Adobe PDF | Öffnen/Anzeigen |
Diese Ressource ist urheberrechtlich geschützt. |
Diese Ressource ist urheberrechtlich geschützt.
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