Adaptive Inertia-Weighted Firefly Algorithm

Real-life optimization problems required more and more technique, which completely utilizes the search spaces to obtain the best optimal solution, so researchers have an opportunity to propose a new technique or a modified version of the existing technique. In this order, this paper is a new modified version of nature-inspired metaheuristic firefly algorithm. FA is swarm intelligence algorithm inspired by flashing pattern and behavior of fireflies. FA has a tendency to trap in local optima and shows a slow convergence for optimization problems. To overcome these problems, in the proposed variant we add an adaptive inertia weight to update the position of search agents. To validate the performance of the proposed variant, it is tested on 23 traditional benchmark functions. The static and numerical results confirm the efficacy of the proposed variant over the original algorithm.

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