The paper "Firefly Algorithm: Recent Advances and Applications" by Xin-She Yang and Xingshi He provides a comprehensive review of the Firefly Algorithm (FA), a nature-inspired metaheuristic algorithm. The authors highlight the algorithm's fundamentals, recent developments, and diverse applications. They emphasize the importance of balancing exploration and exploitation, which is crucial for all metaheuristic algorithms. Through numerical experiments, they demonstrate that the FA outperforms the intermittent search strategy, a landscape-based approach, in terms of efficiency and solution quality. The paper also discusses the algorithm's efficiency in solving multimodal and global optimization problems, particularly in higher dimensions. The authors conclude by noting the growing popularity of nature-inspired algorithms and the need for further research to bridge the gap between theoretical understanding and practical performance, especially in large-scale and combinatorial optimization problems.The paper "Firefly Algorithm: Recent Advances and Applications" by Xin-She Yang and Xingshi He provides a comprehensive review of the Firefly Algorithm (FA), a nature-inspired metaheuristic algorithm. The authors highlight the algorithm's fundamentals, recent developments, and diverse applications. They emphasize the importance of balancing exploration and exploitation, which is crucial for all metaheuristic algorithms. Through numerical experiments, they demonstrate that the FA outperforms the intermittent search strategy, a landscape-based approach, in terms of efficiency and solution quality. The paper also discusses the algorithm's efficiency in solving multimodal and global optimization problems, particularly in higher dimensions. The authors conclude by noting the growing popularity of nature-inspired algorithms and the need for further research to bridge the gap between theoretical understanding and practical performance, especially in large-scale and combinatorial optimization problems.