Volume 5, Issue 3, June 2012, Pages 413 - 420
A Novel Real-coded Quantum-inspired Genetic Algorithm and Its Application in Data Reconciliation
Authors
Lin Gao, Xingsheng Gu
Corresponding Author
Lin Gao
Received 28 March 2011, Accepted 13 February 2012, Available Online 1 June 2012.
- DOI
- 10.1080/18756891.2012.696893How to use a DOI?
- Keywords
- quantum-inspired genetic algorithm, real-coded, interval division, nonlinear data reconciliation
- Abstract
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.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Lin Gao AU - Xingsheng Gu PY - 2012 DA - 2012/06/01 TI - A Novel Real-coded Quantum-inspired Genetic Algorithm and Its Application in Data Reconciliation JO - International Journal of Computational Intelligence Systems SP - 413 EP - 420 VL - 5 IS - 3 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2012.696893 DO - 10.1080/18756891.2012.696893 ID - Gao2012 ER -