Implementation of genetic algorithms. Practical approaches

Abstract

In the paper, the authors analyze the main concepts related to the operation of the Genetic Algorithm in order to find an optimal solution, expressed through the fitness function. By analogy with the evolutionary dimension of Darwin's theory, which involves the generation of populations (generations) of chromosomes, the genetic algorithm involves the selection of the most "efficient", most "adaptable" chromosomes from the current generation. Thus, new chromosomes are formed by applying one of the three genetic operators (or all three): selection, crossover and mutation. In this sense the authors examine the most popular methods related to the implementation of the genetic operators mentioned above. A concrete application of the Genetic Algorithm is examined and at the same time the stopping conditions of the respective algorithm are investigated.