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By combining CMBOA and PSO with quasi-oppositional learning, a cloud estimation of distribution particle swarm optimizer is firstly introduced. Then, it is extended to multi-objective optimization problems by using maximum ranking. In the algorithm's offspring generation scheme, new individuals are generated in the cloud estimation of distribution way or in the PSO way. And instead of Pareto dominance,...
Cloud estimation of distribution particle swarm optimizer combining PSO and cloud model is introduced. In the algorithm's offspring generation scheme, new particles are generated in the cloud estimation of distribution way or in the PSO way. The innovation of the algorithm is production of cloud particles according to the cloud model theory. The cognitive population obtained during optimization is...
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