Journal of Northeastern University ›› 2011, Vol. 32 ›› Issue (9): 1229-1232.DOI: -

• OriginalPaper • Previous Articles     Next Articles

Application of the quantum particle swarm optimization approach in the geometric constraint problems

Cao, Chun-Hong (1); Tang, Chuan (2); Zhao, Da-Zhe (3); Zhang, Bin (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110819, China; (2) State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China; (3) Key Laboratory of Medical Image Computing of Ministry of Education, Northeastern University, Shenyang 110819, China
  • Received:2013-06-19 Revised:2013-06-19 Published:2013-04-04
  • Contact: Cao, C.-H.
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Abstract: Geometric constraint problem is equivalent to the problem of solving a set of nonlinear equations, and the constraint problem can be transformed into an optimization problem. Inspired by the classical PSO method and quantum mechanics theory, this paper presents a novel quantum-behaved PSO (QPSO) to solve geometric constraint problems. In the QPSO model, the state of a particle is depicted by a wave function instead of position and velocity. The advantage of the algorithm is that it can maintain the diversity of the population in the interested problems. The experimental result shows that the algorithm can improve efficiency and convergence of the geometric constraint solutions.

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