Tag: particle swarm optimization

Particle Swarm Optimization (PSO) is a population-based stochastic optimization technique developed by Kennedy and Eberhart in 1995, inspired by the social behavior of bird flocking or fish schooling. PSO simulates the movement of individual particles (solutions) in a search space, where each particle's position is adjusted based on its own experience and the experience of its neighbors. The goal is to find the optimal solution to a given problem by iteratively moving particles towards promising regions of the search space.