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Double Flight-Modes Particle Swarm Optimization

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  • Wang Yong
  • Li Jing-yang
  • Li Chun-lei

Abstract

Getting inspiration from the real birds in flight, we propose a new particle swarm optimization algorithm that we call the double flight modes particle swarm optimization (DMPSO) in this paper. In the DMPSO, each bird (particle) can use both rotational flight mode and nonrotational flight mode to fly, while it is searching for food in its search space. There is a King in the swarm of birds, and the King controls each bird’s flight behavior in accordance with certain rules all the time. Experiments were conducted on benchmark functions such as Schwefel, Rastrigin, Ackley, Step, Griewank, and Sphere. The experimental results show that the DMPSO not only has marked advantage of global convergence property but also can effectively avoid the premature convergence problem and has good performance in solving the complex and high-dimensional optimization problems.

Suggested Citation

  • Wang Yong & Li Jing-yang & Li Chun-lei, 2013. "Double Flight-Modes Particle Swarm Optimization," Journal of Optimization, Hindawi, vol. 2013, pages 1-8, December.
  • Handle: RePEc:hin:jjopti:356420
    DOI: 10.1155/2013/356420
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    References listed on IDEAS

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    1. Jiao, Bin & Lian, Zhigang & Gu, Xingsheng, 2008. "A dynamic inertia weight particle swarm optimization algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 37(3), pages 698-705.
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