Proceedings of the 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)

Research on Planning Methods of Three-dimensional tactical airspace

Authors
Jianbo Wang, Jiacheng Ma
Corresponding Author
Jianbo Wang
Available Online May 2018.
DOI
https://doi.org/10.2991/amcce-18.2018.85How to use a DOI?
Keywords
component; formatting; style; styling;
Abstract
Three-dimensional tactical training Airspace planning is a complex combinatorial optimization problem. It is very important to construct the corresponding model and design the efficient and fast algorithm to improve the efficiency of airspace utilization and training. Aiming at the characteristics of airspace, this paper divides the whole airspace into cubical units. Based on this, the training airspace planning model is constructed, and an improved genetic algorithm is used to find the optimal solution, which excludes a large number of infeasible solutions and improves the convergence rate. The experimental results show that the method is feasible and stable, and has a strong practical value, which can effectively solve the planning problem of 3D tactical training airspace.
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Proceedings
2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
Part of series
Advances in Engineering Research
Publication Date
May 2018
ISBN
978-94-6252-508-5
ISSN
2352-5401
DOI
https://doi.org/10.2991/amcce-18.2018.85How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jianbo Wang
AU  - Jiacheng Ma
PY  - 2018/05
DA  - 2018/05
TI  - Research on Planning Methods of Three-dimensional tactical airspace
BT  - 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/amcce-18.2018.85
DO  - https://doi.org/10.2991/amcce-18.2018.85
ID  - Wang2018/05
ER  -