Abstract
Particle swarm optimization (PSO) is one of the most efficient and popular swarm intelligence-based search algorithms for continuous optimization. PSO provides the solutions probabilistically. Therefore, finding error bound during the search process can help in developing a better PSO. Stability analysis of an algorithm provides the information about error bounds. Stability analysis of PSO with inertia weight and constriction coefficient is carried out by von Neumann stability criterion. Conditions on acceleration parameters, constriction coefficient and inertia weight are obtained for stability.
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