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In this paper, a particle swarm optimization method with a new strategy for inertia weight has been considered. The author abandoned the commonly used linear inertia weight and proposed a new dynamic inertia weight based on fitness of the particles. The new weight is a function of the best and the worst fitness of the particles. The considered NIWPSO algorithm was tested on a set of benchmark functions...
This paper presents an improved particle swarm optimization algorithm (CPSO) in which corrective procedure was introduced. The aim of this corrective procedure is to set new, better velocities for some particles when their present velocities are inefficient. New velocities are the functions of previous and current velocities. The presented algorithm was tested with a set of benchmark functions and...
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