On the Analysis of Self-Adaptive Evolutionary Algorithms

Due to the exibility in adapting to di erent tness 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. Speci cally, population mean and variance of a number of SA-EA operators, such as various realparameter 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-adaptiveGAs and ESs have shown similar performance in the past and also suggest appropriate strategy parameter values which must be chosen while applying and comparing di erent SA-EAs.

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