Dynamic Random Walk and Dynamic Opposition Learning for Improving Aquila Optimizer: Solving Constrained Engineering Design Problems
One of the most important tasks in handling real-world global optimization problems is to achieve a balance between exploration and exploitation in any nature-inspired optimization method.As a result, the search agents of an algorithm constantly strive to investigate the unexplored regions of a search space.Aquila Optimizer (AO) is a recent additio