APPLICATION OF GENETIC ALGORITHM TO SOLVE A CLUSTERING PROBLEM

The article proposes the use of Genetic Algorithm (GA The approach was implemented in Python using some of its libraries and tested in 120 instances. The results were compared to those of the CPLEX solver. The AGs presented superior quality solutions, with shorter average execution times, even under the same time limits. This highlights the efficiency of the method in exploring complex search spaces and avoiding optimal locations, overcoming the limitations of exact methods. The research concludes that AGs are a robust and effective alternative, especially in scenarios with large data volume and time constraints. When the quality of the solution is a priority, the AG proves to be an advantageous choice compared to other methods, reinforcing its potential in practical optimization applications.