ACTA AERONAUTICAET ASTRONAUTICA SINICA >
A Kind of Antiaircraft Weapon-target Optimal Assignment Under Earlier Damage Principle
Received date: 2013-11-25
Revised date: 2014-04-11
Online published: 2014-04-17
Supported by
China Postdoctoral Science Foundation (2012M521833)
In antiaircraft weapon-target assignment, damage time could be delayed under maximum damage principle with firepower resources constraint, when firepower resources are sufficient. To cope with the disadvantage, a new weapon-target assignment model under earlier damage is proposed. In the new model targets with high target threat are firstly assigned to a few weapons, which can damage these targets as early as possible, and the damage probability is greater than the preset threshold. That is to say, by using flying time from target to weapon, the damage time is considered except damage probability and firepower resources, and serious and earlier damage with fewer firepower resources can be achieved at the same time. Based on the new model, a mixed chaos and discrete particle swarm optimization (CDPSO) algorithm is presented to solve the weapon-target assignment problem. The proposed algorithm improves the seeking ability for the global optimal solution, so that the local extremum is avoided. Simulation results show the advantage of the new weapon-target assignment model, as well as the effectiveness and the superiority of the proposed mixed optimization algorithm.
CHEN Li , WANG Zhongxu , WU Zhaobin , WANG Bo . A Kind of Antiaircraft Weapon-target Optimal Assignment Under Earlier Damage Principle[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2014 , 35(9) : 2574 -2582 . DOI: 10.7527/S1000-6893.2014.0048
[1] Zhang Z L, Wu W D. Method of aptitudinally distributing firepower in aerial defence[J]. Fire Control and Command Control, 2006, 31(2): 75-77. (in Chinese) 张自立, 武卫东. 防空智能火力分配的实现方法[J].火力与指挥控制, 2006, 31(2): 75-77.
[2] Huang L W, Xu P G, Wang Q. Firepower distribution problems based on Hungarian method[J]. Fire Control and Command Control, 2007, 32(6): 25-28. (in Chinese) 黄力伟, 许品刚, 王勤. 基于匈牙利算法求解的火力分配问题[J]. 火力与指挥控制, 2007, 32(6): 25-28.
[3] Ruan M Z, Li Q M, Liu T H. Modeling and optimization on fleet antiaircraft firepower allocation[J]. Acta Armamentarii, 2010, 31(11): 1525-1529. (in Chinese) 阮旻智, 李庆民, 刘天华. 编队防空火力分配建模及其优化方法研究[J]. 兵工学报, 2010, 31(11): 1525-1529.
[4] Guo Y H, Li Y T, Yang F Y. Mutation ant colony algorithm for weapon-target assignment problem based on threshold of damage probability[J]. Journal of Gun Launch & Control, 2006(4): 1-5. (in Chinese) 郭蕴华, 李运涛, 杨福缘. 考虑毁伤概率门限的火力分配变异蚁群算法[J]. 火炮发射与控制学报, 2006(4): 1-5.
[5] Yang F, Wang Q, Hou Y Z. Weapon-target assignment in multi-launcher system based on improved integer field particle swarm optimization algorithm[J]. Acta Armamentarii, 2011, 32(7): 906-912. (in Chinese) 杨飞, 王青, 侯砚泽. 基于整数域改进粒子群优化算法的多平台武器目标分配[J]. 兵工学报, 2011, 32(7): 906-912.
[6] Li Y, Dong Y N. Weapon-target assignment based on simulated annealing and discrete particle swarm optimization in cooperative air combat[J]. Acta Aeronautica et Astronautica Sinica, 2010, 31(3): 626-631. (in Chinese) 李俨, 董玉娜. 基于SA-DPSO混合优化算法的协同空战火力分配[J]. 航空学报, 2010, 31(3): 626-631.
[7] Wang Y X, Guo Z. Fire distribution of missile-gun integrated air defense system under earlier damage principle[J]. Acta Armamentarii, 2009, 30(4): 481-485. (in Chinese) 王艳霞, 郭治. 先期毁伤准则下弹炮结合防空武器系统的火力分配[J]. 兵工学报, 2009, 30(4): 481-485.
[8] Liu W D, Jiang Q S, Li Y, et al. Fire distribution of the network centric ship-to-air missile based on earlier damage[J]. Ship Science and Technology, 2011, 33(2): 98-101. (in Chinese) 刘卫东, 姜青山, 李勇, 等. 基于先期毁伤的舰空导弹网络化协同反导火力分配[J]. 舰船科学技术, 2011, 33(2): 98-101.
[9] Lee Z J, Su S F, Lee C Y. Efficiently solving general weapon-target assignment problem by genetic algorithms with greedy eugenics[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2003, 33(1): 113-121.
[10] Luo D L, Duan H B, Wu S X, et al. Research on air combat decision-making for cooperative multiple target attack using heuristic ant colony algorithm[J]. Acta Aeronautica et Astronautica Sinica, 2006, 27(6): 1166-1170. (in Chinese) 罗德林, 段海滨, 吴顺详, 等. 基于启发式蚁群算法的协同多目标攻击空战决策研究[J]. 航空学报, 2006, 27(6): 1166-1170.
[11] Wu X J, Yang Z Z, Zhao M. A uniform searching particle swarm optimization algorithm[J]. Acta Electronica Sinica, 2011, 39(6): 1261-1266. (in Chinese) 吴晓军, 杨战中, 赵明. 均匀搜索粒子群算法[J]. 电子学报, 2011, 39(6): 1261-1266.
[12] Zhang C S, Sun J G, Ouyang D T. A self-adaptive discrete particle swarm optimization algorithm[J]. Acta Electronica Sinica, 2009, 37(2): 299-304. (in Chinese) 张长胜, 孙吉贵, 欧阳丹彤. 一种自适应离散粒子群算法及其应用研究[J]. 电子学报, 2009, 37(2): 299-304.
[13] Sun Y X, Wang Z H, Chen Z Q, et al. Chaotic particle swarm optimization and analysis[J]. Journal of System Simulation, 2008, 20(21): 5920-5923. (in Chinese) 孙艳霞, 王增会, 陈增强, 等. 混沌粒子群优化及其分析[J]. 系统仿真学报, 2008, 20(21): 5920-5923.
[14] Ye W, Zhu A H, Ouyang Z H, et al. Multi-UCAV cooperation mission assignment based on hybrid discrete particle swarm optimization algorithm[J]. Acta Armamentarii, 2010, 31(3): 331-336. (in Chinese) 叶文, 朱爱红, 欧阳中辉, 等. 基于混合离散粒子群算法的多无人作战飞机协同目标分配[J]. 兵工学报, 2010, 31(3): 331-336.
[15] Wang L F, Zeng J C. A cooperative evolutionary algorithm based on particle swarm optimization and simulated annealing algorithm[J]. Acta Automatica Sinica, 2006, 32(4): 630-635. (in Chinese) 王丽芳, 曾建潮. 基于微粒群算法与模拟退火算法的协同进化方法[J]. 自动化学报, 2006, 32(4): 630-635.
[16] Ji Z, Liao H L, Wu Q H. Particle swarm optimization and its application[M]. Beijing: Science Press, 2009: 48-53. (in Chinese) 纪震, 廖惠连, 吴青华. 粒子群算法及应用[M]. 北京: 科学出版社, 2009: 48-53.
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