Optimization of Air Defense System Deployment Against Reconnaissance Drone Swarms

Due to their advantages in flexibility, scalability, survivability, and cost-effectiveness, drone swarms have been increasingly used for reconnaissance tasks and have posed great challenges to their opponents on modern battlefields. This paper studies an optimization problem for deploying air defens...

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Veröffentlicht in:Complex System Modeling and Simulation Jg. 3; H. 2; S. 102 - 117
Hauptverfasser: Li, Ning, Su, Zhenglian, Ling, Haifeng, Karatas, Mumtaz, Zheng, Yujun
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Tsinghua University Press 01.06.2023
Schlagworte:
air defense systems
anti-drone
deployment optimization
drone swarms
evolutionary algorithms
ISSN:2096-9929, 2096-9929
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Zusammenfassung:Due to their advantages in flexibility, scalability, survivability, and cost-effectiveness, drone swarms have been increasingly used for reconnaissance tasks and have posed great challenges to their opponents on modern battlefields. This paper studies an optimization problem for deploying air defense systems against reconnaissance drone swarms. Given a set of available air defense systems, the problem determines the location of each air defense system in a predetermined region, such that the cost for enemy drones to pass through the region would be maximized. The cost is calculated based on a counterpart drone path planning problem. To solve this adversarial problem, we first propose an exact iterative search algorithm for small-size problem instances, and then propose an evolutionary framework that uses a specific encoding-decoding scheme for large-size problem instances. We implement the evolutionary framework with six popular evolutionary algorithms. Computational experiments on a set of different test instances validate the effectiveness of our approach for defending against reconnaissance drone swarms.
ISSN:2096-9929
2096-9929
DOI:10.23919/CSMS.2023.0003