An Improved Genetic Algorithm for Training Airspace Planning

DOI

10.2991/icmmita-16.2016.184How to use a DOI?

Keywords

airspace planning; genetic algorithm; packing optimization

Abstract

Airspace planning of tactical training is a centralized planning, which is typical for Air Force tactical training. Because of the complexity of airspace and the diversity of training courses, artificial packing can't guarantee the utilization rate of airspace. Due to the irregularities of airspace, the minimum horizon merit-based insertion algorithm was proposed based on analysis of BL algorithm considering the reasonable utilization of surrounding airspace; On account of airspace limitation, selection operator, crossover operator and fitness function were established based on basic genetic algorithm, and for the purpose of packing optimization, genetic algorithm and improved packing algorithm were combined. The results show that the algorithm can ensure the utilization of airspace. The above method may provide a scientific basis for airspace planning of tactical training in real life.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jiacheng Ma
AU  - Dengkai Yao
AU  - Guhao Zhao
PY  - 2017/01
DA  - 2017/01
TI  - An Improved Genetic Algorithm for Training Airspace Planning
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 1002
EP  - 1007
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.184
DO  - 10.2991/icmmita-16.2016.184
ID  - Ma2017/01
ER  -