Cuckoo optimization algorithm via Grey wolf optimizer

• COGWO blends cuckoo eggs+migration with wolf moves. • It clusters, spawns variants then refines. • It clamps bounds, caps size, logs best.

• COA exploration: Each agent lays eggs within a local radius tied to search-range and egg share; new eggs are sampled around parents, the worst fraction is discarded, and the population is trimmed back to a fixed size.
• COA migration: The population is clustered into habitats; a focal habitat is chosen by average fitness, and all agents move a controlled step toward its best member with a small random directional deviation.
• GWO exploitation: Inside each habitat, three leaders (alpha, beta, delta) guide the rest; agents update their positions toward the leaders using time-decreasing influence to intensify search near promising areas.
• Hybrid loop & constraints: Each iteration evaluates fitness, clusters, migrates, lays eggs and culls, merges and truncates, then applies the GWO update—while positions are clamped to the variable bounds.
• Convergence tracking: The global best-so-far (strongest alpha across habitats) is updated after the full iteration and logged to produce a monotone convergence curve for minimization.