A Novel Real-coded Quantum-inspired Genetic Algorithm and Its Application in Data Reconciliation

Traditional quantum-inspired genetic algorithm (QGA) has drawbacks such as premature convergence, heavy computational cost, complicated coding and decoding process etc. In this paper, a novel real-coded quantum-inspired genetic algorithm is proposed based on interval division thinking. Detailed comp...

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Veröffentlicht in:International journal of computational intelligence systems Jg. 5; H. 3; S. 413 - 420
Hauptverfasser: Lin, G.A.O., Xingsheng, G.U.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Dordrecht Springer Netherlands 01.06.2012
Springer
Schlagworte:
interval division
nonlinear data reconciliation
quantum-inspired genetic algorithm
real-coded
Research Article
real-coded
quantum-inspired genetic algorithm
nonlinear data reconciliation
interval division
ISSN:1875-6891, 1875-6883, 1875-6883
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Traditional quantum-inspired genetic algorithm (QGA) has drawbacks such as premature convergence, heavy computational cost, complicated coding and decoding process etc. In this paper, a novel real-coded quantum-inspired genetic algorithm is proposed based on interval division thinking. Detailed comparisons with some similar approaches for some standard benchmark functions test validity of the proposed algorithm. Besides, the proposed algorithm is used in two typical nonlinear data reconciliation problems (distilling process and extraction process) and simulation results show its efficiency in nonlinear data reconciliation problems.
ISSN:1875-6891
1875-6883
1875-6883
DOI:10.1080/18756891.2012.696893