Nature inspired metaheuristic algorithms-a comparative review

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Author: 
Rajesh Kumar Sahoo, Deeptimanta Ojha and Satyabrata Dash
Abstract: 

Many metaheuristic algorithms are used for solving different optimization problems efficiently. From these metaheuristic algorithms, nature-inspired optimization algorithms are widely used to find better solutions and their best results. In this paper, five types of metaheuristic algorithms such as Particle swarm optimization (PSO) algorithm, Bee colony optimization (BCO) algorithm, Bat algorithm (BA), Cuckoo search (CS), Firefly algorithms (FA) were used as the basis for comparison. Particle swarm optimization algorithm is based on the interactions between social insect, swarms. The Bee colony optimization algorithm is influenced by the foraging behavior of honey bees. Cuckoo search uses brooding parasitism of cuckoo species and bat algorithm is inspired by the echolocation of microbats. Firefly algorithm is emphasized by the flashing behavior of swarming firefly.

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