Abstract
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. Based on the obtained results, it is shown that population size affects the route length, and the optimal population size for this problem is found to be 150. Using the tournament selection operator, the ordered crossover operator, and the inverse mutation operator, we obtained a salesman's route of 9271.735 km, which, based on the results presented in this paper, is optimal for visiting 29 cities.
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