AbstractApproaches inspired by natural processes have been developed due to their effectiveness in addressing different challenges encountered by Swarm algorithms, such as struggling with local optima, and evolutionary algorithms, such as encountering slow convergence. By integrating evolutionary and swarm intelligence approaches, which is nature-inspired approach, a solution can be achieved that combines the exploration capacity of swarms with the exploitation ability of evolutionary algorithms. This has the potential to enhance overall optimization performance. Therefore, proposing techniques such as bald eagle search (BES), a nature-inspired approach that tackles optimization problems by mimicking the hunting behavior of bald eagles, appears to be beneficial. To our knowledge, there are presently no algorithm that mimic the hunting behavior of bald eagles, which is characterized by group hunting. The BES algorithm involves three stages: selection space, search, and swoop. The evaluation of .....