Swarm Intelligence Algorithm

Swarm intelligence algorithms are computational methods inspired by the collective behavior of social insects or animal groups to solve complex optimization problems. Current research focuses on improving existing algorithms like Particle Swarm Optimization and developing novel approaches such as the Shrike Optimization Algorithm, often addressing limitations like premature convergence to local optima and enhancing performance in multi-objective and discrete optimization scenarios. These algorithms find applications in diverse fields, including machine learning, robotics, and natural language processing, demonstrating their significance for both theoretical advancements and practical problem-solving.