Multivariate Collaborative Development and Comprehensive Classification Evaluation of Airport Cluster Based on Ant Colony Intelligent Optimization Algorithm

  • Juan Yan

Abstract

At present, the functional positioning of various airports in the regional airport clusters of our country has become seriously homogenized. The severe co-directional positioning has led to vicious competition among airports, especially those that are relatively close geographically. In this paper, the super efficiency DEA model, Logit model, and cluster analysis combination classification model for the airport cluster are established based on any colony intelligent optimization algorithm. In addition, the airport cluster in the Pearl River Delta is taken as an example to carry out programming analysis and solve the models. Gradient differentiated positioning is performed on various airports, and the results suggest that: The models are evaluated from different perspectives, and similar conclusions are obtained, which has further verified the effectiveness of the comprehensive classification evaluation. The evaluation result is as the following: Hong Kong > Guangzhou > Shenzhen > Macao > Zhuhai. Finally, Hong Kong and Guangzhou airports are positioned as international hubs, Shenzhen is a regional hub, Hong Kong and Macao are trunk airports. On the basis of the evaluation, the corresponding collaborative development strategy is put forward to achieve the collaborative development of various airports and avoid unnecessary competition in the airline network. At the same time, it can reduce the enormous pressure on air traffic management and further boost the sound development of air transportation.

Published
2020-07-31
How to Cite
Juan Yan. (2020). Multivariate Collaborative Development and Comprehensive Classification Evaluation of Airport Cluster Based on Ant Colony Intelligent Optimization Algorithm. Design Engineering, 829 - 844. https://doi.org/10.17762/de.vi.577
Section
Articles