The State Of The Art Nature Inspired Metaheuristic Algorithms

1444 Words May 1st, 2016 6 Pages
— The paper reviews the state-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. Firefly algorithm is an evolutionary optimization algorithm, and is inspired by the flashing behavior of special flies called fireflies in nature. There are some noisy non-linear mathematical optimization problems that can be effectively solved by Metaheuristic Algorithms. Firefly algorithm is one of the new metaheuristic algorithms for these optimization problems. The algorithm is inspired by the flashing behavior of fireflies. Firefly Algorithm (FA) is a recent nature inspired optimization algorithm, which simulates the flash pattern and characteristics of fireflies. It is a powerful swarm intelligence algorithm inspired by the flashing phenomenon of the fireflies. The optimization results of both PSO and Firefly are analyzed from the results obtained in Matlab and the results are used to compare both the algorithms.

Index Terms— Firefly algorithm, Metaheuristic algorithm, PSO

INTRODUCTION
Most of the conventional or classic algorithms are deterministic. For example, the simplex method in the linear programming is deterministic. Some deterministic optimization algorithms used the gradient information, they are called the gradient-based algorithms. Firefly is a metaheuristic algorithm that is inspired by the…

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