Genetic operators impact on genetic algorithms based variable selection

This paper faces the problem of variables selection through the use of a genetic algorithm based metaheuristic approach. The method is based on the evolution of a population of variables subsets, which is led by the genetic operators determining their selection and improvement through the algorithm generations. The impact of different genetic operators expressly designed for this purpose is assessed through a test campaign. The results show that the use of specific operators can lead to remarkable improvements in terms of selection quality.