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논문검색

A Novel Cultural Quantum-behaved Particle Swarm Optimization Algorithm

원문정보

X. Z. Gao, Ying Wu, Xianlin Huang, Kai Zenger

보안공학연구지원센터(IJHIT) International Journal of Hybrid Information Technology Vol.5 No.2 2012.04 pp.117-122
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초록

영어

A novel cultural quantum-behaved particle swarm optimization algorithm (CQPSO) is proposed to improve the performance of the quantum-behaved PSO (QPSO). The cultural framework is embedded in the QPSO, and the knowledge stored in the belief space can guide the evolution of the QPSO. 15 high-dimensional and multi-modal functions are employed to investigate the proposed algorithm. Numerical simulation results demonstrate that the CQPSO can indeed outperform the QPSO.

목차

Abstract
 1. Introduction
 2. Basic Particle Swarm Optimization and the QPSO
  2.1. Basic Particle Swarm Optimization
  2.2. Quantum-behaved Particle Swarm Optimization
 4. Cultural Quantum-behaved Particle Swarm Optimization
 5. Simulation Results
 Acknowledgements
 References

키워드

저자정보

  • X. Z. Gao Department of Automation and Systems Technology, Aalto University School of Electrical Engineering
  • Ying Wu Center for Control Theory and Guidance Technology, Harbin Institute of Technology
  • Xianlin Huang Center for Control Theory and Guidance Technology, Harbin Institute of Technology
  • Kai Zenger Department of Automation and Systems Technology, Aalto University School of Electrical Engineering

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