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Metaheuristic algorithms are optimization algorithms which attempt to enhance the degree of resolution of the solution space iteratively. This is performed by utilizing guided search methods along with some randomness properties. These algorithms are motivated by biological phenomena or the social behavior of the species. While the deterministic optimization methods depend on the nature of the optimization problem, the metaheuristic algorithms are generally problem independent. Due to their specific advantages over the classical methods, these algorithms have been used extensively in solving the different problems in the fields of science and engineering. One such metaheuristic algorithm is the firefly algorithm. It is inspired by the flashing behavior of fireflies and widely used for solving nonlinear- nonconvex optimization problems. This chapter describes the firefly algorithm and its recent modifications. The …