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A MuIti-Objective ParticIe Swarm Optimization AIgorithm Integrating MuItipIy Strategies
Author(s): 
Pages: 1538-1544
Year: Issue:  8
Journal: Acta Electronica Sinica

Keyword:  particle swarm optimizationintegrating multiply strategiesmulti-objective optimization problemmulti-objective particle swarm optimization algorithm;
Abstract: In order to improve the overall performance of multi-objective particle swarm optimization algorithm (MOPSO) in solving complicated multi-objective optimization problems,a multi-objective particle swarm optimization algorithm integrating multiply strategies (MSMOPSO)was proposed in the paper.A new initialization approach of combining uniformization and random-ization was adopted in the MSMOPSO.Secondly,a disturbance item was added to the particle’s velocity updating formula.Thirdly, a simplified k-nearest neighbor approach was applied to preserve the diversity of external archive.Finally,every non-dominated par-ticle in the external archive was assigned the property of lifespan and the lifespan value would be adjusted dynamically during the run of the MSMOPSO.The experimental results illustrate that the proposed algorithm significantly outperforms the other five peer competitors in terms of GD,SP on ZDT and DTLZ test instances set.
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