Affiliations: [a] College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Jiangsu Nanjing, China
| [b] Jiangsu Police Institute, Jiangsu Nanjing, China
| [c] School of Modern Post, Nanjing University of Posts and Telecommunications, Jiangsu Nanjing, China
Correspondence:
[*]
Corresponding author. Yixiang Sun, College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Jiangsu Nanjing, China. E-mail: sunyixiang1988@hotmail.com.
Abstract: At present, airlines cannot meet the requirements of increasing air cargo volume and cargo service quality by simply improving air transportation capacity. On the basis of increasing the construction of aviation logistics distribution centers, airlines also need to optimize the distribution route. By analyzing and comparing the application of genetic algorithm in the problem of distribution path optimization, this paper proposes a new adaptive genetic algorithm with adaptive mutation to improve the search ability in the local range, which has faster convergence speed than the general genetic algorithm. And solve the logistics node location model. The result proves that the algorithm is faster and more accurate, and can solve the transportation path problem in distribution.
Keywords: Improved genetic algorithm, distribution center, path optimization, aviation logistics
