Authors: Beyer, Hans-Georg
Kalyanmoy Deb
Title: On the Analysis of Self-Adaptive Evolutionary Algorithms
Language (ISO): en
Abstract: Due to the exibility in adapting to different fitness landscapes, self-adaptive evolutionary algorithms (SA-EAs) have been gaining popularity in the recent past. In this paper, we postulate the properties that SA-EA operators should have for successful applications. Specifically, population mean and variance of a number of SA-EA operators, such as various real-parameter crossover operators and self-adaptive evolution strategies, are calculated for this purpose. In every case, simulation results are shown to verify the theoretical calculations. The postulations and population variance calculations explain why self-adaptive GAs and ESs have shown similar performance in the past and also suggest appropriate strategy parameter values which must be chosen while applying and comparing different SA-EAs.
Subject Headings: blend crossover operator
evolution strategies
fuzzy recombination operator
genetic algorithms
population mean
population variance
simulated binary crossover
Issue Date: 2001-10-16
Provenance: Universität Dortmund
Appears in Collections:Sonderforschungsbereich (SFB) 531

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