The Firefly Algorithm offers several advantages in multimodal optimization. Firstly, it can effectively handle problems with multiple global optima by utilizing the concepts of attractiveness and intensity between fireflies. This allows for exploration and exploitation of the search space simultaneously. Secondly, the algorithm is highly scalable and can be easily parallelized, making it suitable for handling large-scale optimization problems. Additionally, the algorithm is relatively simple to implement and has a low computational cost, making it widely applicable in various domains.

One of the main advantages of the Firefly Algorithm is its ability to handle multimodal optimization problems. Unlike other optimization algorithms, it can effectively locate multiple optimal points in the search space simultaneously. This makes it particularly useful in scenarios where the goal is to find multiple solutions instead of just a single global optimum. Furthermore, the Firefly Algorithm is inspired by the behavior of fireflies in nature, which makes it intuitive and easy to understand. This can be beneficial in educational settings and when explaining the algorithm to non-technical stakeholders.