Convergence velocity of an evolutionary algorithm with self-adaptation
Mikhail A. Semenov · Rothamsted Repository (Rothamsted Repository) · 2002
A stochastic Lyapunov function was used to assess the convergence velocity of a simple evolutionary algorithm with self-adaptation, which searches for a maximum of a function. This algorithm uses two types of parameters: parameters belonging to the domain of the function, and strategy parameters, which control changes of fitness parameters. It was shown that the convergence velocity of the evolutionary algorithm with self-adaptation is exponential, similar to the convergence velocity of the optimal deterministic algorithm, the Fibonacci search, on the class of unimodal functions.