Improvement of the Aircraft Traffic Management Advisor Optimization Using a Hybrid Genetic Algorithm

被引：1
|
作者：
Soheili, Adel [1 ]
Mashhadi, Habib Rajabi [1 ,2 ]
机构：
[1] Ferdowsi Univ Mashhad, Dept Elect Engn, Mashhad, Khorasan Razavi, Iran
[2] Ferdowsi Univ Mashhad, Ctr Excellence Soft Comp & Intelligent Informat P, Mashhad, Khorasan Razavi, Iran
来源：
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS | 2016年 / 9卷 / 03期
关键词：
Air traffic control; arriving sequences delays; traffic management advisor; genetic algorithm;
D O I：
10.1080/18756891.2016.1175818
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
During the last decade, problems regarding the Traffic Management Advisor(TMA) has become a concerning matter. A novel hybrid Genetic Algorithm(GA) for the goal of seeking best possible alignment has been presented in this paper. This simple and yet very thorough method benefits from low computational burden, higher convergence rate and lower overall delays. Comprehensive simulations and implementation of the imbedded specially designed rearrangement operator, have shown the effectiveness of the proposed method in comparison with previous literatures and classic GA.
引用
收藏
页码：559 / 571
页数：13
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