Study of the influence of genetic algorithm parameters changing on the solution rate of knapsack problem
The article is about a knapsack problem and a genetic algorithm. The influence of such parameters of the genetic algorithm as the number of calls to the objective function, types of selection, crossing, mutations and generation of generations of the genetic algorithm on the efficiency of finding a solution to the knapsack problem is described. The measure of efficiency is the number of iterations is taken to find the best solution