Improved PSO-based Multi-Objective Optimization using inertia weight and acceleration coefficients dynamic changing, crowding and mutation

@article{Wang2008ImprovedPM,
  title={Improved PSO-based Multi-Objective Optimization using inertia weight and acceleration coefficients dynamic changing, crowding and mutation},
  author={Hui Wang and Feng Qian},
  journal={2008 7th World Congress on Intelligent Control and Automation},
  year={2008},
  pages={4479-4484}
}
This paper proposes a PSO-based multi-objective optimization named as DCMOPSO (dynamic changing multi-objection particle swarm optimization). In this scheme, the inertia weight and acceleration coefficients dynamic changing to explore the search space more efficiently. The crowding distance and mutation operator mechanism also adopted to maintain the diversity of nondominated solutions. The performance of DCMOPSO is investigated by some benchmark functions and compared with MOPSO and NSGA. The… CONTINUE READING

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