population

COMPUTATIONAL COMPLEXITY EVALUATION OF A GENETIC ALGORITHM

The article is devoted to the estimation of computational complexity of a genetic algorithm as one of the key tools for solving optimisation problems. The theoretical aspects of computational complexity of algorithms and the interrelation of elements of a genetic algorithm are considered. The main types of computational complexity of algorithms are described: time, simple and asymptotic. Five basic rules for calculating the asymptotic complexity are given.

Використання генетичних алгоритмів для апроксимації функцій дійсними поліномами

Наведено метод апроксимації функцій поліномами з дійсними степенями, в якому підбір степеня здійснюється за допомогою генетичного алгоритму.

The method of approximation of functions by polynomials with real powers, which is the power of selection with a genetic algorithm.

GENETIC ALGORITHM AS A TOOL FOR SOLVING OPTIMISATION PROBLEMS

The article focuses on the peculiarities of using the genetic algorithm (GA) for solving optimization problems. It provides a classification of optimization problems and offers a detailed description of the structural elements of the GA and their role in solving the traveling salesman problem. To assess the impact of GA parameters on its effectiveness, a study on the influence of population size on the length of the traveling salesman's route is conducted.

EFFECT OF LEMNA MINOR POPULATION DENSITY ON BIOELECTRIC PARAMETERS OF ELECTRO-BIOSYSTEMS

The article presents a study of the influence of Lemna minor population density on the bioelectric potential and current of model electro-biosystems in the laboratory сonditions using 500 and 1000 Ω resistors and in the open circuit. The positive effect of increasing the density of duckweed plants populations from 60 to 120 fronds/ml on the growth of bioelectric parameters of model electro-biosystems under load conditions and without resistors was revealed. Increasing the amount of duckweed biomass is a factor of enhancing the efficiency of electro-biosystems based on L.

Using genetic algorithms for modelling informational processes

In this article genetic algorithms are considered including their types and practical applications. The scientific works of domestic and foreign researchers have been studied. This article presents methods and examples of solving tasks of data mining for genetic algorithms. The description of main components of models of genetic algorithms is presented. A parallel between biological systems and systems aimed at solving technical problems is drawn.