NSGA-Ⅱ 알고리즘을 이용한 KADIZ 감시용 방공레이다 배치 최적화
Optimizing the Deployment of Air Defense Radars for KADIZ Surveillance using NSGA-Ⅱ algorithm
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
This study addresses the problem of optimally deploying air defense radars to improve the aerial surveillance capabilities of the Korean Air Defense Identification Zone (KADIZ). This problem is defined as a multi-objective optimization problem that simultaneously considers the aerial surveillance capability and cost of installing radars. Moreover, a methodology is proposed to review the more realistic detection coverage of a radar, incorporating the theory of radar engineering and terrain obstacles. A non-dominated sorting genetic algorithm (NSGA)-II is proposed as a solution for the multi-objective optimization problem, facilitating the derivation of radar deployment plans that minimize the cost while maximizing the area rate to achieve the target detection probability within the KADIZ.
Abstract
This study addresses the problem of optimally deploying air defense radars to improve the aerial surveillance capabilities of the Korean Air Defense Identification Zone (KADIZ). This problem is defined as a multi-objective optimization problem that simultaneously considers the aerial surveillance capability and cost of installing radars. Moreover, a methodology is proposed to review the more realistic detection coverage of a radar, incorporating the theory of radar engineering and terrain obstacles. A non-dominated sorting genetic algorithm (NSGA)-II is proposed as a solution for the multi-objective optimization problem, facilitating the derivation of radar deployment plans that minimize the cost while maximizing the area rate to achieve the target detection probability within the KADIZ.
참고문헌 (10)
- "Hankyoreh" (2019)[URL]
- C. -Y. Jung, "An Optimal Missile Allocation Problem for Maximizing Kill Probability", Korean Management Science Review, 27(1), pp.75~90 (2010)
- J.-Y. Lee, "The Optimal Allocation Model for SAM Using Multi-Heuristic Algorithm : Focused on Theater Ballistic Missile Defense", IE Interfaces, 21(3), pp.262~273 (2008)
- K. H. Baek, "Study on the Optimal Location of Low Altitude Air Defense Radar", Journal of the Korea Institute of Military Science and Technology, 17(2), pp.248~257 (2014)
- Mu, J., "An Optimization Method of Radar Deployment Based on Detection Probability Combining PSO Algorithm with Variable Weight", Applied Mathematics, Modeling and Computer Simulation, 30, pp.186~194 (2022)
- Cheng, Y., "A Multi-Objective Optimization Method for Radar Deployment Based on an Improved NSGA-II Algorithm", 2023 7th Asian Conference on Artificial Intelligence Technology(ACAIT), pp.46~52 (2023)
- Y. Kim, "Metaheuristic" (2017), Chonnam National University Press
- Y. Chang, "Multi-objective optimization for rapid and robust optimal oilfield development under geological uncertainty", Computational Geosciences, 19, pp.933~950 (2015)
- M. Kotti, "A novel multi-objective algorithm : application to the optimal sizing of current conveyors", 2010 XIth International Workshop on Symbolic and Numerical Methods, Modeling and Applications to Circuit Design(SM2ACD), pp.1~5 (2010)
- Q. Luo, "Multi-objective equilibrium optimizer slime mould algorithm and its application in solving engineering problems", Structural and Multidisciplinary Optimization, 66(5), pp.1~41 (2023)