Nature Inspired Metaheuristic Optimization Algorithms Essay

Nature-Inspired Metaheuristic Optimization Algorithms-A Review Pragati Loomba Sonali Tiwari And Neerja Negi Student, Faculty of Computer Applications Assistant Professor, Faculty of Computer Applications Manav Rachna International University Manav Rachna International University Faridabad Faridabad loombapragati.pl@gmail.com sonali.fca@mriu.edu.in neerja.fca@mriu.edu.in Abstract - Now a day nature-inspired algorithms become a current trend and is applicable to almost every area. This paper provides a wide classification of existing algorithms as the basis of future research.. This paper reviewed the existing algorithms Firefly Algorithm (FA), Ant Colony Optimization (ACO), Bat Algorithm (BA), Cuckoo Search (CS) and Other Nature Inspired Algorithms. However, the study reveals the existing algorithms to improve the optimization performance in different analysis. The purpose of this review and comparison is to present a analysis of all the nature inspired algorithms and to motivate the researchers. Keyword -Nature Inspired Algorithms, Evolutionary Algorithm, Stochastic global search algorithm , Swarm Intelligence, Bio-Inspired Algorithms. I. INTRODUCTION Nature has the ability to solve and optimize the complex problem by logical and effective ways. Nature has provided us the intelligence ,self learning , pattern recognition, optimization etc. The mostly followed nature-inspired models of computation are genetic algorithm, neural computation, and evolutionaryShow MoreRelatedThe State Of The Art Nature Inspired Metaheuristic Algorithms1444 Words   |  6 Pagesstate-of-the-art nature inspired metaheuristic algorithms in optimization, including the Firefly algorithm, PSO algorithms and ABC algorithm. By implementing them in Matlab, we will use worked examples to show how each algorithm works. 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