• DocumentCode
    671540
  • Title

    An application of quantum-inspired particle swarm optimization to function optimization problems

  • Author

    Tazuke, Koichiro ; Muramoto, Noriyuki ; Matsui, Nobuyuki ; Isokawa, T.

  • Author_Institution
    Grad. Sch. of Eng., Univ. of Hyogo, Himeji, Japan
  • fYear
    2013
  • fDate
    4-9 Aug. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Quantum-Inspired Particle Swarm Optimization (QPSO) is an extension of Particle Swarm Optimization (PSO) methods, in which the concept of quantum mechanics is adopted. The state of a particle in QPSO is described by a wave function derived from the Schrödinfer equation, whereas a particle in standard PSOs has its location and velocity as its state. The performances of QPSOs are demonstrated through the optimization problem for higher-dimensional functions, with comparison of the standard PSO. The experimental results show that QPSOs can find (near) optimal values much faster than the conventional PSO.
  • Keywords
    particle swarm optimisation; quantum computing; quantum theory; QPSO; Schrödinger equation; function optimization problems; quantum mechanics; quantum-inspired particle swarm optimization; wave function; Density functional theory; Optimization; Particle swarm optimization; Probabilistic logic; Standards; Wave functions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2013 International Joint Conference on
  • Conference_Location
    Dallas, TX
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4673-6128-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2013.6706880
  • Filename
    6706880