Parallel Multi-Swarm PSO Based on K-Medoids and Uniform Design

  title={Parallel Multi-Swarm PSO Based on K-Medoids and Uniform Design},
  author={Jie Zhang and Yuping Wang and Junhong Feng},
PAM (Partitioning around Medoid) is introduced to divide the swarm into several different subpopulations. PAM is one of k-medoids clustering algorithms based on partitioning methods. It attempts to divide n objects into k partitions. This algorithm overcomes the drawbacks of being sensitive to the initial partitions in kmeans algorithm. In the parallel PSO algorithms, the swarm needs to be divided into several different smaller swarms. This study can be excellently completed by PAM. The aim of… CONTINUE READING
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Publications referenced by this paper.
Showing 1-10 of 22 references

Coello Coello . MRMOGA : A new parallel multi - objective evolutionary algorithm based on the use of multiple resolutions

  • A. Carlos
  • Concurr . Comput . Pract . Exp .
  • 2007
1 Excerpt

Inertia weight in particle swarm optimization

  • F. Yong, T. Gui-Fa, W. Ai-Xin, Y. Yong-Mei
  • 2nd International Conference on Innovative…
  • 2007
1 Excerpt

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