基于分配策略优化算法的智能防空任务分配

doi:10.16182/j.issn1004731x.joss.22-0432

系统仿真学报 ›› 2023, Vol. 35 ›› Issue (8): 1705-1716.doi: 10.16182/j.issn1004731x.joss.22-0432

基于分配策略优化算法的智能防空任务分配

刘家义¹^,²(), 王刚¹, 付强¹(), 郭相科¹, 王思远¹^,²

^1. 空军工程大学防空反导学院，陕西西安 710051
^2. 空军工程大学研究生院，陕西西安 710051

收稿日期:2022-04-29 修回日期:2022-06-30 出版日期:2023-08-25 发布日期:2023-08-15
第一作者简介:
刘家义(1996-)，男，博士生，研究方向为深度强化学习、智能辅助决策。E-mail：sixandone1@163.com
基金资助:
国家自然科学基金(62106283)

Intelligent Air Defense Task Assignment Based on Assignment Strategy Optimization Algorithm

Jiayi Liu¹^,²(), Gang Wang¹, Qiang Fu¹(), Xiangke Guo¹, Siyuan Wang¹^,²

^1. Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China
^2. Graduate College, Air Force Engineering University, Xi'an 710051, China

Received:2022-04-29 Revised:2022-06-30 Online:2023-08-25 Published:2023-08-15

摘要/Abstract

关键词: 分配策略优化算法, 任务分配, 马尔可夫决策过程, 深度强化学习, 智能体

Key words: assignment strategy optimization algorithm, task assignment, Markov decision process, deep reinforcement learning, agent

刘家义,王刚,付强等 . 基于分配策略优化算法的智能防空任务分配[J]. 系统仿真学报, 2023, 35(8): 1705-1716.

Jiayi Liu,Gang Wang,Qiang Fu,et al . Intelligent Air Defense Task Assignment Based on Assignment Strategy Optimization Algorithm[J]. Journal of System Simulation, 2023, 35(8): 1705-1716.

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参考文献 31

1	Zhang Jiandong, Chen Yuyang, Yang Qiming, et al. Dynamic Task Allocation of Multiple UAVs Based on Improved A-QCDPSO[J]. Electronics, 2022, 11(7): 1028.
2	Wang Yao, Shi Yongkang, Liu Yunhui. Research on Improved Genetic Simulated Annealing Algorithm for Multi-UAV Cooperative Task Allocation[J]. Journal of Physics: Conference Series, 2022, 2246(1): 012081.
3	Ma Yingying, Wang Guoqiang, Hu Xiaoxuan, et al. Two-stage Hybrid Heuristic Search Algorithm for Novel Weapon Target Assignment Problems[J]. Computers & Industrial Engineering, 2021, 162: 107717.
4	Kong Lingren, Wang Jianzhong, Zhao Peng. Solving the Dynamic Weapon Target Assignment Problem by an Improved Multiobjective Particle Swarm Optimization Algorithm[J]. Applied Sciences, 2021, 11(19): 9254.
5	王幸运, 田野, 强晓明, 等. 基于协同效能的反导作战任务分配模型[J]. 空军工程大学学报(自然科学版), 2013, 14(4): 27-31.
	Wang Xingyun, Tian Ye, Qiang Xiaoming, et al. Mission Assignment Model for Anti-missile Combat Based on Cooperative Efficiency[J]. Journal of Air Force Engineering University(Natural Science Edition), 2013, 14(4): 27-31.
6	姜欢, 陈万春. 防空作战动静态武器目标分配初步研究[J]. 飞行力学, 2007, 25(4): 90-93.
	Jiang Huan, Chen Wanchun. Dynamic and Static Weapon-target Assignments of Air Defense[J]. Flight Dynamics, 2007, 25(4): 90-93.
7	Hosein P, Walton J, Athansm. Dynamic Weapon Target Assignment Problems With Vulnerable C2 Nodes[J]. Proceedings of the Command & Control Symposium, 1988, 1: 1-10.
8	Hosein P, Athans M. Preferential Defense Strategies, Part 1: The Static Case[R]. MITLaboratory for Information and Decision Systemswith Partial Support, Cambridge, MA, Tech. Rep, 1990.
9	韩松臣, 秦俊奇, 韩品尧, 等. 马尔可夫决策过程在目标分配中的应用[J]. 哈尔滨工业大学学报, 1996, 28(2): 32-36.
	Han Songchen, Qin Junqi, Han Pinyao, et al. An Application of the Markov Decision Process to Target Assignment[J]. Journal of Harbin Institute of Technology, 1996, 28(2): 32-36.
10	杨进帅, 李进, 王毅. 武器-目标分配问题研究[J]. 火力与指挥控制, 2019, 44(5): 6-11.
	Yang Jinshuai, Li Jin, Wang Yi. Study of Weapon Target Assignment Problem[J]. Fire Control & Command Control, 2019, 44(5): 6-11.
11	Zhou Wenhong, Liu Zhihong, Li Jie, et al. Multi-target Tracking for Unmanned Aerial Vehicle Swarms Using Deep Reinforcement Learning[J]. Neurocomputing, 2021, 466: 285-297.
12	He Lei, Aouf N, Song Bifeng. Explainable Deep Reinforcement Learning for UAV Autonomous Path Planning[J]. Aerospace Science and Technology, 2021, 118: 107052.
13	刘传波, 邱志明, 吴玲, 等. 动态武器目标分配问题的研究现状与展望[J]. 电光与控制, 2010, 17(11): 43-48.
	Liu Chuanbo, Qiu Zhiming, Wu Ling, et al. Review on Current Status and Prospect of Researches on Dynamic Weapon Target Assignment[J]. Electronics Optics & Control, 2010, 17(11): 43-48.
14	邱鸿泽. 基于自适应大邻域搜索算法的武器-目标分配问题研究[D]. 长沙: 国防科技大学, 2018.
	Qiu Hongze. Weapon Target Assignment Research Based on Adaptive Large Neighborhood Search[D]. Changsha: National University of Defense Technology, 2018.
15	韩松臣. 导弹武器系统效能分析的随机理论方法[M]. 北京: 国防工业出版社, 2001.
	Han Songchen. Stochastic Theory and Method for Effectiveness Analysis of Missile Weapon Systems[M]. Beijing: National Defense Industry Press, 2001.
16	陈英武, 蔡怀平, 邢立宁. 动态武器目标分配问题中策略优化的改进算法[J]. 系统工程理论与实践, 2007, 27(7): 160-165.
	Chen Yingwu, Cai Huaiping, Xing Lining. An Improved Algorithm of Policies Optimization of Dynamic Weapon Target Assignment Problem[J]. Systems Engineering-Theory & Practice, 2007, 27(7): 160-165.
17	何鹏, 周德云, 王谦. 多UCAV任务分配有限阶段MDP方法和算法[J]. 火力与指挥控制, 2012, 37(10): 99-101, 104.
	He Peng, Zhou Deyun, Wang Qian. Finite Stage MDP for Task Allocation in UCAVs Cooperative Control[J]. Fire Control & Command Control, 2012, 37(10): 99-101, 104.
18	Ma Qiaoyun, Liu Tongsheng. Modeling Task Allocation in MAS With MDP[C]//The 15th International Conference on Industrial Engineering and Engineering Management(IE&EM'2008). Zhengzhou: Chinese Mechanical Engineering Society, 2008: 581-585.
19	Hyytiä Esa, Righter R, Aalto S. Task Assignment in a Heterogeneous Server Farm With Switching Delays and General Energy-aware Cost Structure[J]. Performance Evaluation, 2014, 75-76: 17-35.
20	Girard J, Reza Emami M. Concurrent Markov Decision Processes for Robot Team Learning[J]. Engineering Applications of Artificial Intelligence, 2015, 39: 223-234.
21	韦刚, 高嘉乐, 孙文. 多目标-多武器系统目标分配模型与算法研究[J]. 飞航导弹, 2016(5): 77-82.
22	Yue Longfei, Yang Rennong, Zhang Ying, et al. Deep Reinforcement Learning for UAV Intelligent Mission Planning[J]. Complexity, 2022, 2022: 3551508.
23	Shi Yuchun, Zheng Hao, Li Kang. Data-driven Joint Beam Selection and Power Allocation for Multiple Target Tracking[J]. Remote Sensing, 2022, 14(7): 1674.
24	Park J H, Farkhodov K, Lee S H, et al. Deep Reinforcement Learning-based DQN Agent Algorithm for Visual Object Tracking in a Virtual Environmental Simulation[J]. Applied Sciences, 2022, 12(7): 3220.
25	Sasaki H, Horiuchi T, Kato S. Experimental Study on Behavior Acquisition of Mobile Robot by Deep Q-network[J]. Journal of Advanced Computational Intelligence and Intelligent Informatics, 2017, 21(5): 840-848.
26	Yang Yang, Li Juntao, Peng Lingling. Multi-robot Path Planning Based on a Deep Reinforcement Learning DQN Algorithm[J]. CAAI Transactions on Intelligence Technology, 2020, 5(3): 177-183.
27	Seliman S M S, Sadek A W, He Qing. Automated Vehicle Control at Freeway Lane-drops: A Deep Reinforcement Learning Approach[J]. Journal of Big Data Analytics in Transportation, 2020, 2(2): 147-166.
28	Huang Hongji, Yang Yuchun, Wang Hong, et al. Deep Reinforcement Learning for UAV Navigation Through Massive MIMO Technique[J]. IEEE Transactions on Vehicular Technology, 2020, 69(1): 1117-1121.
29	杨晨, 张少卿, 孟光磊. 多无人机协同任务规划研究[J]. 指挥与控制学报, 2018, 4(3): 234-248.
	Yang Chen, Zhang Shaoqing, Meng Guanglei. Multi-UAV Cooperative Mission Planning[J]. Journal of Command and Control, 2018, 4(3): 234-248.
30	付强, 王刚, 鲁伟超, 等. 防空反导智能指控探索与实践[C]//第八届中国指挥控制大会论文集. 北京: 兵器工业出版社, 2020: 44-49.
	Fu Qiang, Wang Gang, Lu Weichao, et al. Exploration and Practice of Intelligent Command and Control of Air Defense and Antimissile[C]//Proceedings of the 8th Chinese Conference on Command and Control. Beijing: Weapon Industry Press, 2020: 44-49.
31	Schulman J, Wolski F, Dhariwal P, et al. Proximal Policy Optimization Algorithms[EB/OL]. (2017-08-28) [2022-03-23]. 1707.06347.

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基于分配策略优化算法的智能防空任务分配

Intelligent Air Defense Task Assignment Based on Assignment Strategy Optimization Algorithm

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