A comparative study of continuous multimodal global optimization using PSO, FA and Bat Algorithms

Abstract This paper introduces the nature-inspired metaheuristic algorithms for optimization of standard Benchmark function, including Firefly algorithm, PSO algorithms and Bat algorithm. We have implemented these algorithms in MATLAB. We have considered here how this algorithms work on continuous multimodal global optimization benchmark function. All these are the evolutionary nature inspired optimization metaheuristic algorithms and are inspired by the nature. to find out optimal solutions of continuous, multimodel Benchmark function. The stimulation results of this experiment were analyzed and compared to the best solutions found and compare with time. So the Bat algorithm in each continuous, multimodel Benchmark function optimization function seems to perform better and efficient.