An Improved Genetic Algorithm for Training Airspace Planning
- 10.2991/icmmita-16.2016.184How to use a DOI?
- airspace planning; genetic algorithm; packing optimization
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.
- © 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/).
Cite this article
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 -