Experimental study of the dependence of the convergence rate of the genetic algorithm on its parameters

The definition of the genetic algorithm is given, and different variants of its construction are studied. The genetic algorithm is considered as an optimization method for a function defined in an arbitrary set, and its convergence rate is defined as a stochastic function of the vector of parameters, Experiments were performed with the model of the genetic algorithm with the aim to iind different relations. The model of the combined genetic algorithm was developed, i.e., the genetic algorithm that modifies parameters of another genetic algorithm, and in experiments with it, the vector of optimal characteristics is studied. As a result, the set of optimal parameters is obtained.