Particle Swarm Optimization (PSO) is an evolutionary algorithm used for solving optimization problems. It simulates a population of particles, each particle having a position and velocity vector in the search space of the problem. The particles move around in the search space interacting with each other and the environment, gradually approaching an optimal solution. PSO has been successfully applied to a wide range of optimization problems including machine learning, logistics and scheduling, engineering design, and many more.