SexualGA: Gender-Specifc Selection for Genetic Algorithms

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Selection for reproduction in the context of Genetic Algorithms uses only one selection scheme to select parent individuals. When considering the model of sexual selection in the area of population genetics it gets obvious that the process of choosing mating partners in natural populations is different for male and female individuals. In this paper the authors introduce a new selection paradigm for Genetic Algorithms (SexualGA) based upon the concepts of male vigor and female choice of population genetics which provides the possibility to use two different selection schemes simultaneously within one algorithm. By using this new concept it is possible to simulate sexual selection in natural populations more precisely. Furthermore, SexualGA also offers far more flexibility concerning the adaptivity of selection pressure enabling the GA user to tune the algorithm more accurately.
Original languageEnglish
Title of host publicationProceedings of the 9th World Multi-Conference on Systemics, Cybernetics and Informatics (WMSCI) 2005
PublisherInternational Institute of Informatics and Systemics
Publication statusPublished - 2005
Event9th World Multi-Conference on Systemics, Cybernetics and Informatics (WMSCI) 2005 - Orlando, United States
Duration: 10 Jul 200513 Jul 2005


Conference9th World Multi-Conference on Systemics, Cybernetics and Informatics (WMSCI) 2005
Country/TerritoryUnited States


  • Genetic Algorithms
  • Selection
  • Selection Pressure
  • Population Genetics


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