Comparison Of Firefly Photinus Algorithm With Tidal Force Firefly Algorithm For Global Optimisation

- Particle Swarm Optimization (PSO) is a widely used metaheuristics algorithm based on thecollective movement of birds or such species. Firefly algorithm (FA) is a modification of conventionalPSO and getting high acceptance in engineering problems due to faster convergence and robustness.But there is a serious drawback of getting trapped into local optima with FA. A balance betweenexploitation and exploration is necessary for avoiding such a situation. This paper investigates furthermodification to FA to avoid this limitation. Two such modifications are considered for examination,Firefly Photinus Algorithm (FPA) and Tidal Force Firefly Algorithm (TFFA). FPA is based on thebehaviour of Photinus fireflies and is developed by incorporating a forbidden mate list into thealgorithm. A time-dependent absorption coefficient is also introduced. In TFFA the firefly attractionis modified by the tidal force equation. The concept of opposition-based Reinforcement Learning isalso included in the algorithm for minimizing the bias due to the initial selection of thepopulation. Four standard benchmark optimization functions are used for testing the algorithms. BothFPA and TFFA give good convergence with TTFA having an edge over the other.