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
Link To Document :
بازگشت