Butterfly algorithm with Lèvy Flights for global optimization

In recent years, various nature-inspired algorithms have been developed for solving complex real world problems with multiple constraints. These algorithms have shown remarkable performance which is the main reason of their preference over other conventional optimization algorithms. In this paper, a novel nature-inspired optimization algorithm based on the food foraging of butterflies is proposed. In the proposed algorithm, the butterflies act as search agents for finding food by sensing different fragrances from various flowers. The proposed algorithm is validated against various benchmark functions and then compared with some well-known nature-inspired algorithms. The results confirm superior performance of the proposed algorithm over other algorithms in solving global optimization problems.