Also known as: Particle Swarm Optimisation
Particle swarm optimization is a population-based optimization method inspired by collective behavior in groups such as flocks or swarms. Candidate solutions move through the search space using both their own best-known positions and the best-known positions found by the group.
A computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. It solves a problem by having a population of candidate solutions, here dubbed particles, and moving these particles around in the search-space according to simple mathematical formulae over the particle's position and velocity. Each particle's movement is influenced by its local best known position, but is also guided toward the best known positions in the search-space, which are updated as better positions are found by other particles. This is expec