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Particle swarm optimization (PSO) often traps in the local optimal solutions. In this paper, an opposition-based disturbance procedure was introduced into a basic PSO, which was abbreviated as PSOOD. For this proposed algorithm, opposition-based disturbance was implemented according to the probability when the personal best position was updated for each particle. Such procedure not only avoids the...
To overcome premature searching by standard particle swarm optimization (PSO) algorithm, a new modified PSO with information of the closest particle is proposed. In the algorithm, the particle is updated not only by the best previous position and the best position among all the particles in the swarm, but also by the best previous position of the closest particle. To balance the trade-off between...
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