Unified particle swarm delivers high efficiency to particle swarm optimization

Display Omitted The proposed unified particle swam (UPS) greatly improves particle swarm optimization (PSO).The UPS uses a unification factor to balance the effects of cognitive and social terms of PSO.UPS particles are expected to move toward the center of its personal best and the global best.Three types of experiments on 13 benchmark functions were conducted.Improvements of UPS upon PSO are effective on two kinds of PSO variants. This paper suggests integrating a unification factor into particle swarm optimization (PSO) to balance the effects of cognitive and social terms. The resultant unified particle swarm (UPS) moves particles toward the center of its personal best and the global best. This improves on PSO, which moves particles far beyond the center. Widely used benchmark functions and four types of experiments demonstrate that the proposed UPS uses slightly more computational time than PSO to attain significantly higher efficiency and, usually, better solution effectiveness and consistency than PSO. Robust performance was further demonstrated by the significantly higher efficiency and better solution effectiveness and stability achieved by the UPS, as compared to the PSO and its variants. Outstandingly, convergence speeds for the proposed UPS were very good on the 13 benchmark functions examined in experiment 1, demonstrating the correct movement of UPS particles toward convergence.

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