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Particle swarm optimization (PSO) has shown its good performance in many optimization problems. However, PSO could often easily fall into local minima because the particles could quickly converge to a position by the attraction of the best particles. Under this circumstance, all the particles could hardly be improved. This paper presents a hybrid PSO (AMPSO) to solve this problem by applying a novel...
Particle Swarm Optimization (PSO) is a stochastic optimization approach that originated from earlier attempts to simulate the behavior of birds and was successfully applied in many applications as an optimization tool. Estimation of distributions algorithms (EDAs) are a class of evolutionary algorithms which build a probabilistic model capturing the search space properties and use this model to generate...
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