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
Link To Document