Butterfly Optimization Algorithm: A Novel Approach for Global Optimization with MATLAB Implementation

"Butterfly Optimization Algorithm: A New Method for Global Optimization" is a research paper presenting an innovative metaheuristic algorithm for solving global optimization problems. The algorithm demonstrates superior performance in handling complex optimization challenges through its unique simulation of butterfly foraging behavior. The implementation employs key mechanisms including fragrance computation, global search phase with random flight patterns, and local search phase with targeted neighborhood exploration. The provided MATLAB code features core functions such as fragrance intensity calculation, population initialization, and adaptive switching between exploration and exploitation phases. With DOI https://doi.org/10.1007/s00500-018-3102-4, the complete resource package contains both the original paper and executable MATLAB scripts, enabling researchers to thoroughly understand the algorithm's mechanics and extend its application to various domains. The algorithm's versatility makes it particularly suitable for applications in communications systems, control engineering, robotics, and other optimization-intensive fields, offering substantial potential for both theoretical research and practical implementations. The code structure includes modular components for fitness evaluation, position updating, and convergence monitoring, facilitating easy customization for specific problem domains.