A new firefly algorithm with improved global exploration and convergence with application to engineering optimization

Firefly algorithm (FA) is a powerful and efficient meta-heuristic which has shown effective performance in the recent literature when applied to solving engineering optimization problems. FA imitates flashing behavior of fireflies. generates solutions randomly assumes them as However, these algorithms may suffer from premature convergence poor global exploration used optimize complex high dimension Therefore, this study proposed novel FA, called firefly 1 3 (FA1 → 3), via different types movements fireflies an attempt improve characteristics FA. A comprehensive been carried out on CEC2014 test functions compare FA1 with standard several modern improved validate its performance. The experimental results demonstrate that achieved acceptable In addition, it six real-world problems show capability, robustness, efficacy comparison As per simulations, provided suitable higher accuracy than traditional modified introduced last years. According significantly robust dealing various finds design variables straightforwardly. • new movement model for first time constructed. state-of-the-art review Artificial Intelligence techniques reported. Efficiency demonstrated. models are compared. used.