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Particle Swarm Optimization: A Tutorial

Particle Swarm Optimization (PSO) is a technique used to explore the search space of a given problem to find the settings or parameters required to maximize a particular objective. This technique, first described by James Kennedy and Russell C. Eberhart in 1995 [1], originates from two separate concepts: the idea of swarm intelligence based off the observation of swarming habits by certain kinds of animals (such as birds and fish); and the field of evolutionary computation. This short tutorial first discusses optimization in general terms, then describes the basics of the particle swarm optimization algorithm.