Abstract
Study the particle swarm optimization algorithm for solving multi-objective optimization problems. This paper presents a set select space of multi-objective particle swarm optimization algorithm (SMOPSO) based on the Pareto dominate relations, using the method of fast sort to construct non-dominated solution set, pre-set an upper limit of non-dominated solution space, and set an external set to save the optimal solutions. At the same time introduce genetic algorithm crossover and mutation operator for each generation of the updated part of the particles in order to increase the diversity of particle groups, so we can get good distribution of particles. The simulation results verify the validity of this method.
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Shiman, X., Xinzhi, S. (2011). Multi-Objective Optimization Method Based on PSO and Quick Sort. In: Liu, C., Chang, J., Yang, A. (eds) Information Computing and Applications. ICICA 2011. Communications in Computer and Information Science, vol 244. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27452-7_34
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DOI: https://doi.org/10.1007/978-3-642-27452-7_34
Publisher Name: Springer, Berlin, Heidelberg
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