An Experimentation of Firefly Algorithm Using a Different Set of Objective Functions

The Firefly Algorithm (FA) is a well-known meta-heuristic optimization technique inspired by firefly flashing behavior. This paper compares the effectiveness of the firefly algorithm when evaluated with various objective functions. This paper discusses an overview of the firefly algorithm, covering its essential features and underlying ideas. The mathematical formulation and all the different algorithms that are being used are provided with proper description and details as it is used in the process of parameter tuning. To assess the efficacy of the firefly algorithm, a diverse range of objective functions offered by many scientists are used. The objective functions employ several parameters, the values of which are adjusted in relation to other parameters. The experimental findings are examined and displayed in a variety of tabular formats, which include all of the best and worst values of the individual objective functions. The comparison studies indicate the firefly algorithm’s strengths and drawbacks in various optimization objective functions, which shows an efficient result when alternative values are used.