ABSTRACT
Gray wolves in a gray wolf population are divided into head wolf α, deputy leader β, common wolves δ, and underclass wolves ω according to the class mechanism. In addition, the lower the class is, the larger is the number of individuals. To capture a prey, other individuals besiege the prey in an organized manner under the leadership of head wolf α. In the GWO algorithm, the individual with the highest fitness in the group is defined as α and those whose fitness is ranked second and third are defined as β and δ. In addition, others are described as ω. Moreover, the position of the prey is defined as the global optimal solution of an optimizing problem. In a D-dimensional searching space, if the position of the ith wolf is X Xi id( )X X Xi i iD , represents the position of the ith wolf in the d-dimensional space.
