A Genetic Algorithm to Obtain Consistency in Analytic Hierarchy Process

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.