• DocumentCode
    575321
  • Title

    Searching ability of qubit-inspired genetic algorithm

  • Author

    Muramoto, Noriyuki ; Matsui, Nobuyuki ; Isokawa, Teijiro

  • Author_Institution
    Gradute Sch. of Eng., Univ. of Hyogo, Kobe, Japan
  • fYear
    2012
  • fDate
    20-23 Aug. 2012
  • Firstpage
    443
  • Lastpage
    446
  • Abstract
    Qubit-inspired Genetic Algorithm (QGA) is an extension of genetic algorithm in which quantum mechanics and its representations are introduced. A chromosome in our QGA is concretized as a series of quantum-bit (qubit) described by its complex-valued representation, and phase-rotation gates are embedded into the selection process over generations. In our previous work, it has been shown that this scheme has better performances than the classical ones in several problems such as N-K landscape problem, Knapsack Problem, Maximum Search, and Construction of image filters. In this paper, we make clear the effectiveness of the QGA by comparing QGA with GA through minimum solution problem on De Jong´s functions.
  • Keywords
    Turing machines; cellular biophysics; genetic algorithms; knapsack problems; quantum computing; De Jong functions; N-K landscape problem; QGA; chromosome; complex-valued representation; image filters; knapsack problem; maximum search; phase-rotation gates; quantum mechanics; quantum-bit; qubit-inspired genetic algorithm; searching ability; Biological cells; Biological neural networks; Educational institutions; Genetic algorithms; Quantum computing; Sociology; Statistics; Complex-valued representation; De Jong´s function; Genetic Algorithm; Minimum solution problem; Qubit-inspired;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE Annual Conference (SICE), 2012 Proceedings of
  • Conference_Location
    Akita
  • ISSN
    pending
  • Print_ISBN
    978-1-4673-2259-1
  • Type

    conf

  • Filename
    6318480