This paper presents a hybrid algorithm that combines Fuzzy Logic Controller (FLC) and Genetic Algorithms (GAs) and its application\non a traffic signal system. FLCs have been widely used in many applications in diverse areas, such as control system, pattern\nrecognition, signal processing, and forecasting. They are, essentially, rule-based systems, in which the definition of these rules and\nfuzzy membership functions is generally based on verbally formulated rules that overlap through the parameter space.They have\na great influence over the performance of the system. On the other hand, the Genetic Algorithm is a metaheuristic that provides a\nrobust search in complex spaces. In this work, it has been used to adapt the decision rules of FLCs that define an intelligent traffic\nsignal system, obtaining a higher performance than a classical FLC-based control. The simulation results yielded by the hybrid\nalgorithm show an improvement of up to 34% in the performance with respect to a standard traffic signal controller, Conventional\nTraffic Signal Controller (CTC), and up to 31% in the comparison with a traditional logic controller, FLC.
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