Abstract
The basic selection ideas of the different representatives of evolutionary algorithms are sometimes quite diverse. The selection concept of genetic algorithms (GAs) and genetic programming (GP) is basically realized by the selection of above-average parents for reproduction whereas evolution strategies (ES) use the fitness of newly evolved offspring as the basis for selection (survival of the fittest due to birth surplus). This contribution considers aspects of population genetics and Evolution Strategies in order to propose an enhanced and generic selection model for Genetic Algorithms which is able to preserve the alleles which are part of a high quality solution. Some selected aspects of these enhanced techniques are discussed exemplarily on the basis of travelling salesman benchmark (TSP) benchmark problem instances.
Original language | English |
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Title of host publication | Proceedings of the 20th European Modeling and Simulation Symposium |
Publisher | DIPTEM University of Genova |
Pages | 59-68 |
ISBN (Print) | 978-88-903724-0-7 |
Publication status | Published - 2008 |
Event | International Mediterranean and Latin American Modeling Multiconference (I3M 2008) - Campora San Giovanni, Italy Duration: 17 Sep 2008 → 19 Sep 2008 http://www.liophant.org/i3m/ |
Conference
Conference | International Mediterranean and Latin American Modeling Multiconference (I3M 2008) |
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Country/Territory | Italy |
City | Campora San Giovanni |
Period | 17.09.2008 → 19.09.2008 |
Internet address |
Keywords
- softcomputing
- evolutionary computation
- selection
- self adaptation