SHADE (algorithm)

SHADE (Self-adaptive Differential Evolution) is an optimization algorithm designed to find the best solutions in complex problems. It improves upon traditional methods by automatically adjusting its strategies during the search process, enhancing efficiency and effectiveness. SHADE uses a population of candidate solutions that iteratively evolve through combinations and mutations, guided by performance feedback. Its self-adaptive nature allows it to dynamically select the most suitable parameters, making it versatile for various optimization tasks such as engineering design or machine learning. Overall, SHADE balances exploration and exploitation to efficiently identify optimal or near-optimal solutions.