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In this paper, a novel firefly algorithm (FA) is presented to reduce the dependency on parameters. The new FA algorithm is called dynamic step factor based FA (DSFFA), in which the step factor is not fixed and it is dynamically updated during the evolution. Experimental study on several classical benchmark functions show that DSFFA is superior to the basic FA and three other FAs.
Particle swarm optimization and its modifications appear premature convergence for complex optimization problem, because particles' performance becomes same in seeking later period. In this paper, a new model is proposed to avoiding particles' performance same and possessing strong exploration capacity. Considering exploration and exploitation capacity diverse in different stage, the particle swarm...
Particle swarm optimization and its modification for two sub-swarms exchange appear premature convergence for complex optimization problem, because particles' performance becomes same in seeking later period. Therefore, in this paper, a modified two sub-swarms exchange particle swarm optimization is proposed. The particle swarm is divided into two identical sub-swarms, with the first adopting the...
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