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 realised 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 ES in order to propose an enhanced and generic selection model for GAs 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 the Travelling Salesman Benchmark (TSP) problem instances.
|Number of pages||11|
|Journal||International Journal of Simulation and Process Modelling|
|Publication status||Published - Apr 2010|
- Evolutionary computation
- Genetic algorithms selection
- Self adaptation
- Soft computing