INVESTIGATION OF THE IMPACT OF POPULATION SIZE ON THE PERFORMANCE OF A GENETIC ALGORITHM
V.A. Tsygankov, Шабалина Ольга Аркадьевна, A. V. Kataev · Известия Южного федерального университета. Технические науки · 2024
The paper investigates ways to determine the population size in a genetic algorithm and studies therelationship between the number of individuals and the speed of the algorithm. Methods for determiningthe optimal number of individuals in a population by different methods are described: depending on thesize of the chromosomes, for a tree-like type of chromosomes, in the presence of a noise factor and by themethod of a neighboring element with a maximum and minimum boundary. The data obtained by performingeach method differ from each other, for this reason, an assessment was made in order to verify theaccuracy of theoretical data by comparing them with experimental ones. To conduct experiments, a program was developed on the Unity graphics platform with the ability to change the number of individuals inthe population. After receiving the results, the experimental data were compared with the data obtained onthe basis of methods for determining the population size in the genetic algorithm from the first part of thework. The experiment showed that the optimal population size lies in the range of 100-160 individuals.With a decrease in their number, the execution time of the task begins to increase significantly, and withan increase beyond the calculated limit, the reduction in execution time does not correspond to the computingresources expended. The experimental data obtained themselves have the smallest error with themethod used by the tree representation of chromosomes. The results of the study can be used to select thesize of the population during training in order to achieve a better ratio of computing power to learningspeed, and a method defined in the course of work can help in theoretical calculations