RESEARCH OF THE EFFICIENCY OF THE GENETIC ALGORITHM WITH VARIOUS
METHODS OF SELECTION, CROSSOVER TYPES AND STRATEGIES OF FORMATION OF GENERATIONS IN SEARCHING OF EXTREMUMS OF TEST FUNCTIONS
V.S. Maraev, E.A. Bezzubenko, D.A. Cherkashin, A.S. Mihalev
In this article the analysis of materials on genetic algorithms is carried out. The main ideas and principles underlying work of genetic algorithms are considered. The basic stages of the classical genetic algorithm work are analyzed in detail. The review of the most common methods of selection (roulette and tournament), types of crossover (single-point and uniform) and strategies of formation of generations (classical and elitist) is executed.
On test functions the research of genetic algorithm with different methods of selection, types of crossover and strategy of formation of generations is carried out. For each type of algorithm, an estimate of the probability of finding a true solution is given. The received results of the experiments are carefully analyzed. The advantages and disadvantages of different methods of selection, types of crossover, strategy of formation of generations are revealed. The recommendations on the expediency of using genetic algorithms in various situations are stated. The possible directions for further research are defined.
Keywords: genetic algorithm, global extremum, population, generation, selection, crossover, De Jong’s function, Rosenbrock’s function, Rastrigin’s function.