Genetic algorithms

This chapter introduces the basic concepts and notation of genetic algorithms, which is a basic search methodology that can be used for modelling and simulation of complex non-linear dynamical systems. Since this technique can be considered as general purpose optimization methodologies, we can use them to find the mathematical model which minimizes the fitting errors for a specific problem. On the other hand, we can also use this technique for simulation if we exploit their efficient search capabilities to find the appropriate parameter values for a specific mathematical model. We can use a genetic algorithm to optimize the number of rules or the membership functions of a fuzzy system for a specific problem. These are two important application of genetic algorithms, which will be used in later chapters to design intelligent systems for controlling real-world dynamical systems.