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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| Vydáno v: | Complex System Modeling and Simulation Ročník 3; číslo 2; s. 102 - 117 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Tsinghua University Press
01.06.2023
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| ISSN: | 2096-9929, 2096-9929 |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Li, Ning Zheng, Yujun Karatas, Mumtaz Ling, Haifeng Su, Zhenglian |
| Author_xml | – sequence: 1 givenname: Ning surname: Li fullname: Li, Ning organization: Hangzhou Normal University,School of Information Science and Technology,Hangzhou,China,311121 – sequence: 2 givenname: Zhenglian surname: Su fullname: Su, Zhenglian organization: Army Engineering University,College of Field Engineering,Nanjing,China,210007 – sequence: 3 givenname: Haifeng surname: Ling fullname: Ling, Haifeng organization: Army Engineering University,College of Field Engineering,Nanjing,China,210007 – sequence: 4 givenname: Mumtaz surname: Karatas fullname: Karatas, Mumtaz organization: Turkish Naval Academy, National Defense University,Industrial Engineering Department,Tuzla,Turkey,34940 – sequence: 5 givenname: Yujun surname: Zheng fullname: Zheng, Yujun organization: Hangzhou Normal University,School of Information Science and Technology,Hangzhou,China,311121 |
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| Title | Optimization of Air Defense System Deployment Against Reconnaissance Drone Swarms |
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