Year: 2025
Type: article
Abstract: Selection is often considered as a fundamental force in the evolutionary process. Genetic drift, or selection noise, is an important characteristic of selection methods. It has a direct effect on the performance of genetic algorithms. In this paper, a brief review of methods to analyze genetic drift is given, and known estimations of selection noise of various selection schemes used in genetic algorithms are presented. After that, genetic drift of widely used proportional, ranking, and tournament selection schemes is thoroughly studied. To this end, two new measures for selection noise analysis are proposed, namely the noise takeover time and pure reproduction rate. Using these measures, the effect of population size, chromosome length, and selection scheme parameters on genetic drift is analyzed. Also, selection schemes known as being selection pressure equivalent are tested for selection noise equivalence. Both theoretical and experimental approaches are used for the analysis. The results obtained are presented in tabular form. Wherever possible, it is indicated whether the obtained results are identical or different from the results of previous studies. Since no comprehensive study of selection noise has been conducted previously, this indication concerns only some of the results. Although our results differ at some points from those presented earlier, they are consistent on both measures.
Source: Soft Computing
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,190
OpenAlex ID: W4410429422