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Particle swarm optimization (PSO) has been recently adopted to solve constrained optimization problems. In this paper, a cultural-based constrained PSO is proposed to incorporate the information of the objective function and constraint violation into four sections of the belief space, specifically normative knowledge, spatial knowledge, situational knowledge, and temporal knowledge. The archived information...
This paper presents a novel cultural algorithm, in which an adaptive Cauchy mutated particle swarm optimizer (ACMPSO) is used as a population space; the Cauchy allows larger mutations and in this way producing more diversified individuals and covering more major space. The knowledge sources contained in the belief space are specifically designed according to the ACMPSO evolution features. Different...
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