A novel quantum genetic algorithm and its application

Author

Sheng, Zhang ; Wanlu, Jiang

Author_Institution

Hebei Provincial Key Lab. of Heavy Machinery Fluid Power Transm. & Control, Yanshan Univ., Qinhuangdao, China

fYear

2012

fDate

29-31 May 2012

Firstpage

613

Lastpage

617

Abstract

Aiming at the disadvantages of the fixed rotation angle in quantum genetic algorithm (QGA), in this paper, the particle swarm optimization (PSO) was used to update the angle of quantum rotation gate in stead of the old one that locates the angle of quantum rotation gate by a designed query table. According to the experimental results, the novel quantum genetic algorithm (NQGA) with new updating method has got a higher global search capability than common QGA. The NQGA was used to the load distribution optimization of tandem cold rolling. The comparison data show that the NQGA is an effective method for load distribution optimization of tandem cold rolling.

Keywords

genetic algorithms; particle swarm optimisation; quantum computing; query processing; NQGA; PSO; QGA; fixed rotation angle; global search capability; load distribution optimization; novel quantum genetic algorithm; particle swarm optimization; quantum rotation gate; query table; tandem cold rolling; Convergence; Genetic algorithms; Logic gates; Optimization; Particle swarm optimization; Quantum computing; Schedules; load distribution; particle swarm optimization; quantum genetic algorithm; quantum rotation gate;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2012 Eighth International Conference on

Conference_Location

Chongqing

ISSN

2157-9555

Print_ISBN

978-1-4577-2130-4

Type

conf

DOI

10.1109/ICNC.2012.6234602

Filename

6234602