Abstract
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.
Highlights
In recent years, with the rapid development of China and the improvement of household consumption level, aviation demand has increased enormously in China
Lee and Yang [3] analyze the strategy of Incheon Airport to be the logistic center of Northeast Asia; the results show that the key is whether Incheon Airport could attract sufficient global logistic service suppliers
This paper is structured as follows: firstly, the evaluation index system of airport competitiveness is built; secondly, a new algorithm is proposed in which BP neural network is optimized by improved double chains quantum genetic algorithm (IDCQGA-BP); Thirdly, the real data of 8 Chinese airports in Yangtze River Delta region is applied to do the empirical study
Summary
With the rapid development of China and the improvement of household consumption level, aviation demand has increased enormously in China. Park [4] builds index system from the aspects of service, demand, management, facility and regional space, evaluates the static competitiveness of the main airports in East Asia through multilayer decision model. Yeh et al [5] build index system from the aspects of operational management, airport facility and consumer service quality, analyze the static competitiveness of eleven Asia-Pacific airports through fuzzy multiple attribute evaluation method. This paper is structured as follows: firstly, the evaluation index system of airport competitiveness is built; secondly, a new algorithm is proposed in which BP neural network is optimized by improved double chains quantum genetic algorithm (IDCQGA-BP); Thirdly, the real data of 8 Chinese airports in Yangtze River Delta region is applied to do the empirical study. The results show that the new algorithm has good applicability
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