Abstract
This paper exemplarily points out how essential
genetic information evolves during the runs of certain selected GA-variants. The discussed algorithmic enhancements to a standard genetic algorithm certify the survival of essential genetic
information by supporting the survival of relevant alleles rather than the survival of above average chromosomes. This is achieved by defining the survival probability of a new child chromosome
depending on the child’s fitness in comparison to the fitness values of its own parents. The described kind of analysis assumes the knowledge of the unique global optimal solution and is therefore restricted to rather theoretical considerations The main aim of
this paper is to explain the most important properties of the discussed algorithm variants in a rather intuitive way. Aspects for meaningful and practically more relevant generalizations as well as more sophisticated experimental analyses are indicated.
Originalsprache | Englisch |
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Titel | INES 2010 - 14th International Conference on Intelligent Engineering Systems, Proceedings |
Herausgeber (Verlag) | IEEE |
Seiten | 13-18 |
Seitenumfang | 6 |
ISBN (Print) | 9781424476527 |
DOIs | |
Publikationsstatus | Veröffentlicht - 2010 |
Veranstaltung | 14th IEEE International Conference on Intelligent Engineering Systems INES 2010 - Las Palmas, Spanien Dauer: 5 Mai 2010 → 7 Okt. 2010 http://www.ines-conf.org/ines-conf/2010.html |
Publikationsreihe
Name | INES 2010 - 14th International Conference on Intelligent Engineering Systems, Proceedings |
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Konferenz
Konferenz | 14th IEEE International Conference on Intelligent Engineering Systems INES 2010 |
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Land/Gebiet | Spanien |
Ort | Las Palmas |
Zeitraum | 05.05.2010 → 07.10.2010 |
Internetadresse |