Abstract
In some cases, it’s not enough to consider only the objective function of the global optimal point, but also the character of this point and its nearby area. To this end, the concept of practicably optimal point is introduced in this paper. Further, a novel intelligence method named simulated particle swarm optimization (NSPSO) algorithm is proposed to obtain the practicably optimal points according to different requirements. The optimization results reveal that the NSPSO algorithm has strong convergence and stability, and appears to be an efficient alternative for obtaining the practicably optimal points according to different requirements.
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