Abstract
A review of the bio-inspired optimization methods used in the design of type-2 fuzzy systems, which are relatively novel models of imprecision, is considered in this chapter. The fundamental focus of the work is based on the basic reasons for the need for optimization of type-2 fuzzy systems for different areas of application. Recently, bio-inspired methods have emerged as powerful optimization algorithms for solving complex problems. In the case of designing type-2 fuzzy systems for particular applications, the use of bio-inspired optimization methods has helped in the complex task of finding the appropriate parameter values and structure of fuzzy systems. In this chapter, we consider the application of genetic algorithms, particle swarm optimization, and ant colony optimization as three different paradigms that help in the design of optimal type-2 fuzzy systems. We also provide a comparison of the different optimization methods for the case of designing type-2 fuzzy systems.
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