Recent advances on the use of meta-heuristic optimization.pdf

<div>Finding the appropriate values of parameters</div><div>and structure of type-2 fuzzy logic systems is a difficult and</div><div>complex task. Many types of meta-heuristic algorithms</div><div>have been used to find the complex structure and appropriate</div><div>parameter values of the type-2 fuzzy systems and</div><div>more recently hybrid meta-heuristic algorithms. In this</div><div>paper, we review recent advances (2012 to date) on the</div><div>application of meta-heuristic algorithms and hybrid metaheuristic</div><div>algorithms, for the optimization of type-2 fuzzy</div><div>logic systems in intelligent control. It was found that the</div><div>major meta-heuristic algorithms used for optimizing the</div><div>design of type-2 fuzzy logic systems in intelligent control</div><div>were genetic algorithms and particle swarm optimization as</div><div>well as hybrid meta-heuristic algorithms. Researchers can</div><div>use this review as a starting point for further advancement</div><div>as well as an exploration of other meta-heuristic algorithms</div><div>that have received little or no attention from researchers.