A new hybrid nature-inspired metaheuristic for problem solving based on the Social Interaction Genetic Algorithm employing Fuzzy Systems

This paper has the purpose to present a new hybrid nature inspired metaheuristic developed based on three fundamentals pillars extremely well known: Genetic Algorithms, Game Theory and Fuzzy Systems. This new approach tries to mimic a little bit more closer how a population of individuals evolves along time, like human social evolution emphasizing the social interaction between individuals and the non-binary behavior of human decision making against the classical cooperate-defect behavior present in the Prisoner's Dilemma (PD), for example. In this way it is presented the Social Interaction Genetic Algorithm (SIGA), to establish the necessary basis for the application of fuzzy concepts to get the F-SIGA Algorithm. Besides that, it is also presented the structure of an individual more complex with a genotype composed of two chromosomes, one for the solution of the problem and the other representing its behavior's strategy, which could be binary or fuzzy. At least the F-SIGA approach is presented in details, including all its steps. And finally some results are presented to an instance of the Traveling Salesman Problem.