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Mathematical Problems in Engineering
Volume 2013 (2013), Article ID 309750, 8 pages
Research Article

The Evaluation of Dynamic Airport Competitiveness Based on IDCQGA-BP Algorithm

1Transportation Management College, Dalian Maritime University, No. 1 Linghai Road, Dalian 116026, China
2Faculty of Management and Economics, Dalian University of Technology, No. 2 Linggong Road, Dalian 116024, China

Received 25 August 2013; Accepted 30 November 2013

Academic Editor: Daoyi Dong

Copyright © 2013 Qiang Cui et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Aimed at the multidimensional and complex characteristic of airport competitiveness, a new algorithm is proposed in which BP neural network is optimized by improved double chains quantum genetic algorithm (IDCQGA-BP). The new algorithm is better than existing algorithms in convergence and the diversity of quantum chromosomes. The empirical data of eight airports in Yangtze River Delta in 2011 and 2012 is applied to verify the feasibility of the new algorithm, and then the competitiveness of the eight airports from 2013 to 2015 is gotten through the algorithm. The results show the following. (1) The new algorithm is better than the existing optimization algorithms in the aspects of error accuracy and run time. (2) The gaps of the airports in Yangtze River Delta are narrowing; the competition and cooperation are getting stronger and stronger. (3) The main increase reason of airport competitiveness is the increase of own investment.