PSO Algorithm

Particle Swarm Optimization (PSO) is a metaheuristic algorithm inspired by the social behavior of bird flocking, aiming to efficiently find optimal solutions in complex search spaces. Current research focuses on improving PSO's balance between exploration and exploitation, often through hybrid approaches combining PSO with other algorithms like deep reinforcement learning, bee algorithms, or Hamiltonian Monte Carlo methods, and by incorporating adaptive strategies to control population diversity. These advancements enhance PSO's performance across diverse applications, including UAV path planning, cryptographic function design, and water resource monitoring, demonstrating its value as a robust optimization tool in various scientific and engineering domains.