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.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

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  - Proceedings of the 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
PB  - Atlantis Press
SP  - 491
EP  - 496
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  -