This work presents a proposition to solve the problem of inconsistency in Analytic Hierarchy
Process (AHP) matrices using genetic algorithms. Decision matrices resulting from an application
of AHP can be considered an effective method to structure and represent relevant information of
a strategic problem. Inconsistency in the results is a real and frequent possibility. In this case, the
results obtained would become ineffective considering the objectives of the model, which means
no gains in decision making. The Genetic Algorithms are probabilistic search computer models
which are based on the mechanics of natural selection and genetics, combining the concepts of
selective adaptation and survival of the fittest. They are considered to be a powerful technique of
stochastic optimization and, probably the most important evolutionary computer techniques. Its
application to the AHP matrices case allows the detection of inconsistent matrices, while offers
alternative solutions to the decision-maker.