Impactos do operador transgênico na otimização de funções matemáticas utilizando algoritmos genéticos

Abstract

Genetic Algorithms are metaheuristic search and optimization tools inspired by the principles of genetics and evolution. Variations of the Genetic Algorithm have emerged to quicken the discovery of optimal solutions and reduce computational costs. The Transgenic Genetic Algorithm is a variation of the Conventional Genetic Algorithm that incorporates the concepts of transgenesis through the transgenic genetic operator. In order to investigate its potential to improve convergence accuracy and quality in the optimization of mathematical formulas with genetic algorithms, this research evaluates the respective advantages and disadvantages of using the Transgenic Genetic Algorithm and the Conventional Genetic Algorithm in the optimization of mathematical formulas with multiple local optima. The results of the experiments demonstrated that the transgenic operator increased the convergence capacity and reduced the processing time in the optimization of mathematical formulas using genetic algorithms.