Volume 37, Number 5, October 2019
|Page(s)||992 - 999|
|Published online||14 January 2020|
Application of Improved Quantum Genetic Algorithm in Optimization for Surface to Air Anti-Radiation Hybrid Group Force Deployment
Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China
2 Rocket Force University of Engineering Xi'an 710025, China
In this paper, the concept and force deployment needs for anti-electronic jamming and defensing air of surface to air anti-radiation hybrid group was presented, the relationship between shield angle, deployment distance and effective electronic interference etc, were analyzed in the background of air raid battle which is with electronic support, force deployment optimization model of surface to air anti-radiation hybrid group was built based on the kill zone target function. In terms of the characteristic of hybrid group force deployment, quantum genetic algorithm (QGA) was improved with self-adaption rotation angle, the problem which was based on a living example was solved with improved QGA. By contrast, the improved QGA is better in the respects of global optimization, rate of convergence and stability than QGA, particle swarm optimization algorithm and quantum vortex algorithm in the problem of optimization for surface to air anti-radiation hybrid group force deployment.
Key words: quantum genetic algorithm / surface to air ati-radiation / hybrid group / force deployment / Q-gate
关键字 : 量子遗传算法 / 地空反辐射 / 混编群 / 兵力配置 / 量子旋转门
© 2019 Journal of Northwestern Polytechnical University. All rights reserved.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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