About the influence of features of fitness-functions on the convergence of the genetic algorithm

I.O. Lukianov, F.A. Lytvynenko


The adaptive capabilities of a parallel version of a multipopulation genetic algorithm are considered depending on the characteristics of certain classes of fitness-functions. Ways are proposed to increase the rate of convergence to the optimal solution based on effective control of algorithm parameters and strategies for the exchange of chromosome-solutions between populations. The results of computer experiments with the optimization of fitness-functions with various ratios of insignificant and significant factors are presented. The dependence of the convergence rate of the algorithm in the presence of a random effect on the values of fitness-functions is studied.

Problems in programming 2020; 2-3: 362-367


multipopulation genetic algorithm; insignificant factors; computational model

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