协同目标分配问题研究综述

doi:10.16182/j.issn1004731x.joss.19-FZ0382

摘要/Abstract

摘要： 简要剖析了作战协同的概念和内涵,阐述了协同目标分配问题的历史由来及其在指挥与控制流程中的定位。综合分析了协同目标分配问题在模型建立和求解算法上的研究现状,指出了当前研究存在的不足,提出了下一步应将研究重心转向动态、对抗条件下的大规模协同目标分配问题上去,且应重点关注算法的实时性、适应性和迭代进化机制。

关键词: 作战协同, 协同目标分配, 武器目标分配, 动态, 对抗, 智能算法

Abstract: The concept and connotation of combat coordination are briefly analyzed. The historical origin of cooperative target allocation and its orientation in command and control process are expounded. The research status of collaborative target allocation in model building and algorithm solving is analyzed comprehensively, the shortcomings of current research is pointed out. It is proposed that for the next step we should pay more attention to large-scale collaborative target allocation under dynamic and confrontational conditions, and focus on the real-time, adaptability and iterative evolution mechanism of the algorithm.

Key words: combat coordination, cooperative target assignment, Weapon Target Assignment, dynamic, confrontation, intelligent algorithm

中图分类号:

TP391.9

欧峤, 贺筱媛, 陶九阳. 协同目标分配问题研究综述[J]. 系统仿真学报, 2019, 31(11): 2216-2227.

Ou Qiao, He Xiaoyuan, Tao Jiuyang. Overview of Cooperative Target Assignment[J]. Journal of System Simulation, 2019, 31(11): 2216-2227.

参考文献

[1] 张明星, 程光权, 刘忠, 等. 多武器协同作战发射时序规划方法[J]. 指挥与控制学报, 2017, 3(1): 10-18.
Zhang Mingxing, Cheng Guangquan, Liu Zhong, et al.Schedule of Launch Sequential Timing in Multiple Weapons Cooperative Engagement[J]. Journal of Command and Control, 2017, 3(1): 10-18.
[2] 蔡怀平, 陈英武. 武器-目标分配问题研究进展[J]. 火力与指挥控制, 2006, 32(12): 11-15.
Cai Huaiping, Chen Yingwu.The Development of the Research on Weapon-Target Assignment Problem[J]. Fire Control & Command Control, 2006, 32(12): 11-15.
[3] 赫尔曼·哈肯. 高等协同学[M]. 郭治安译. 北京: 科学出版社, 1989.
Hermann Haken.Higher Synergetics[M]. Guo Zhian's Translation. Beijing: Science Press, 1989.
[4] 特鲁申. 关于协同的本质问题[Z]. 总参谋部军训部, 译外军军事期刊译编, 2015.
Trushen. On the Essence of Synergy[Z]. Military Training Department of the General Staff, Translation. Translated Editor of Foreign Military Journals, 2015.
[5] 中国人民解放军国防大学. 联合作战基本理论[Z]. 北京: 国防大学出版社, 2017.
National Defense University of the People's Liberation Army. Basic Theory of Joint Operations[Z]. Beijing: National Defense University Press, 2017.
[6] 胡晓峰, 荣明. 关于联合作战规划系统的几个问题[J]. 指挥与控制学报, 2017, 3(4): 273-280.
Hu Xiaofeng, Rong Ming.Several Questions about Joint Operations Planning System[J]. Journal of Command and Control, 2017, 3(4): 273-280.
[7] Lloyd S P, Witsenhausen H S.Weapons Allocation is NP-Complete[C]. IEEE Summer Conference on Simulation. Reno, Nevada, 1986.
[8] Hosein P A, Walton J T, Athans M.Dynamic weapon-target assignment problems with vulnerable C2 nodes[J]. Proceedings of the Command & Control Symposium (S2577-1604), 1988: 1786-1795.
[9] Khosla D.Hybrid genetic approach for the dynamic weapon-target allocation problem[J]. Proceedings of SPIE the International Society for Optical Engineering (S0277-786X), 2001: 244-259.
[10] Adnan Y, Ron L W, Hee S H, et al.The Generalized Weapon Target Assignment Problem[C]. 10^th International Command and Control Research and Technology Symposium, the Future of C2, June 13-16. McLean, VA: Lockheed Martin Corporation. 2005.
[11] Shima T, Rasmussen S J, Sparks A G, et al.Multiple task assignments for cooperating uninhabited aerial vehicks using genetic algorithms[J]. Computers & Operations Research(S0305-0548), 2006, 33(11): 3252-3269.
[12] 王士同, 刘征. 动态武器目标分配问题的DWTA-GA算法[J]. 华东船舶工业学院学报, 1999, 13(5): 17-22.
Wang Shitong, Liu Zheng.DWTA-GA Algorithm for Dynamic Weapon Target Allocation[J]. Journal of East China Institute of Shipbuilding Industry, 1999, 13(5): 17-22.
[13] 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.Random Theory Method for Effectiveness Analysis of Missile Weapon Systems[M]. Beijing: National Defense Industry Press, 2001.
[14] 蔡怀平, 刘靖旭, 陈英武. 动态武器目标分配问题的马尔可夫性[J]. 国防科学技术大学学报, 2006, 28(3): 124-127.
Cai Huaiping, Liu Jingxu, Chen Yingwu.Markov Property of Dynamic Weapon Target Allocation[J]. Journal of National University of Defense Science and Technology, 2006, 28(3): 124-127.
[15] 李勇君, 黄卓, 郭波, 等. 武器-目标分配问题综述[J]. 兵工自动化, 2009, 28(11): 1-9.
Li Yongjun, Huang Zhuo, Guo Bo, et al.Summary of Weapon-Target Assignment[J]. Military Automation, 2009, 28(11): 1-9.
[16] 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): 43-49.
Liu Chuanbo, Qiu Zhiming, Wu Ling, et al.Research Status and Prospect of Dynamic Weapon Target Allocation[J]. Electro-optic and control, 2010, 17(11): 43-49.
[17] 叶青松, 胡笑旋, 马华伟. 多无人机编队协同目标分配的两阶段求解方法[J]. 合肥工业大学学报(自然科学版), 2015(10): 1431-1436.
Ye Qingsong, Hu Xiaoxuan, Ma Huawei.Two-stage Solution Method for Multi-UAV Formation Cooperative Target Allocation[J]. Journal of Hefei University of Technology (Natural Science Edition), 2015(10): 1431-1436.
[18] 毛昭军, 李云芝, 蔡业泉. 防空作战中合同网协议分布式目标分配算法[J]. 火力与指挥控制, 2008, 33(1): 90-93.
Mao Zhaojun, Li Yunzhi, Cai Yequan.Distributed Target Assignment Algorithms for Contract Network Protocol in Air Defense Operations[J]. Firepower and Command Control, 2008, 33(1): 90-93.
[19] 唐苏妍, 梅珊, 朱一凡, 等. 基于扩展合同网协议的分布式武器目标分配方法[J]. 火力与指挥控制, 2011, 33(3): 568-574.
Tang Suyan, Messan, Zhu Yifan, et al.Distributed Weapon Target Allocation Method based on Extended Contract Network Protocol[J]. Firepower and Command Control, 2011, 33(3): 568-574.
[20] 肖玉杰, 李杰, 刘方. 基于合同网的分布式动态任务分配算法[J]. 舰船科学技术, 2015, 37(3): 113-118.
Xiao Yujie, Li Jie, Liu Fang.Distributed Dynamic Task Allocation Algorithm based on Contract Network[J]. Ship Science and Technology, 2015, 37(3): 113-118.
[21] 黎子芬, 李相民, 代进进, 等. 编队对地动态联合火力分配建模与仿真研究[J]. 系统仿真学报, 2013, 25(12): 2900-2905.
Li Zifen, Li Xiangmin, Dai Jinjin, et al.Research of Modeling and Simulation on Formation Attack to Ground Dynamic Joint Fire Distribution[J]. Journal of System Simulation, 2013, 25(12): 2900-2905.
[22] 腾讯AI研究院. 人工智能[M]. 北京: 中国人民大学出版社, 2017: 94-98.
Tencent AI Research Institute. Artificial Intelligence[M]. Beijing: Renmin University Press, 2017: 94-98.
[23] Hopfield J, Tank D W.Neural Computation of Decisions in Optimization Problems[J]. Biological Cybernetics (S1432-0770), 1985, 52(14): 141-152.
[24] Wacholder E.A Neural Network-based Optimization Algorithm for the Weapon-Target Assignment[R]. DE89-007879, 1989.
[25] Stephen Lucci, Danny Kopec.人工智能[M]. 林赐译. 北京: 人民邮电出版社, 2018: 291-331.
Stephen Lucci, Danny Kopec.Artificial Intelligence[M]. Lin Zhi, Translation. Beijing: People's Posts and Telecommunications Press, 2018: 291-331.
[26] 吴坤鸿, 詹世贤. 分布式遗传模拟退火算法的火力打击目标分配优化[J]. 智能系统学报, 2017, 12(4): 89-92.
Wu Kunhong, Zhan Shixian.Distributed Genetic Simulated Annealing Algorithm for Fire Target Allocation Optimization[J]. Journal of Intelligent Systems, 2017, 12(4): 89-92.
[27] 陈曼, 周凤星. 改进粒子群算法的舰载武器目标分配[J]. 火力与指挥控制, 2018, 43(11): 72-76.
Chen Man, Zhou Fengxing.Shipborne Weapon Target Assignment based on Improved Particle Swarm Optimization[J]. Firepower and command control, 2018, 43(11): 72-76.
[28] 王连山. 关于遗传、蚁群、禁忌搜索算法的比较[J]. 电脑编程技巧与维护, 2009(24): 18-21.
Wang Lianshan.Comparisons of Genetic, Ant Colony and Tabu Search Algorithms[J]. Computer programming skills and maintenance, 2009(24): 18-21.
[29] 蔡怀平, 陈英武, 邢立宁. SVNTS算法的动态武器目标分配问题研究[J]. 计算机工程与应用, 2006(31): 7-10.
Cai Huaiping, Chen Yingwu, Xing Lining.Research on Dynamic Weapon Target Assignment Based on SVNTS Algorithms[J]. Computer Engineering and Applications, 2006 (31): 7-10.
[30] 徐加强, 毕义明, 汪民乐, 等. 基于时空约束的常规导弹火力分配建模与实现[J]. 系统工程与电子技术, 2011, 33(9): 2025-2029.
Xu Qiang, Bi Yiming, Wang Minle, et al.Modeling and Implementation of Conventional Missile Fire Distribution based on Space-time Constraints[J]. Systems Engineering and Electronic Technology, 2011, 33(9): 2025-2029.
[31] Holland J.Adaptation in Natural and Artificial Systems[M]. Ann Arbor, MI: University of Michigan, 1975.
[32] 陈成, 邢立宁, 谭跃进. 求解多机协同任务规划的改进遗传算法[J]. 兵工自动化, 2010, 29(9): 28-31.
Chen Cheng, Xing Lining, Tan Yuejin.Improved Genetic Algorithm for Solving Multi-machine Cooperative Task Planning[J]. Military Automation, 2010, 29(9): 28-31.
[33] 杨山亮, 黄健, 刘洋, 等. 基于遗传算法的联合火力WTA问题研究[J]. 计算机仿真, 2012, 29(3): 61-64.
Yang Shanliang, Huang Jian, Liu Yang, et al.Research on Joint Firepower Weapon Target Assignment Problem Based on Genetic Algorithms[J]. Computer Simulation, 2012, 29(3): 61-64.
[34] 费凯, 杨任农, 黄震宇, 等. 考虑时间约束的空战编队协同火力分配研究[J]. 计算机工程与应用, 2016, 52(13): 259-264.
Fei Kai, Yang Rennong, Huang Zhenyu, et al.Study on Cooperative Fire Distribution of Air Combat Formation Considering Time Constraints[J]. Computer Engineering and Application, 2016, 52(13): 259-264.
[35] 王少蕾, 陈维义, 顾雪峰. 自适应差分进化算法求解多平台多武器-目标分配问题[J]. 系统工程与电子技术, 2013, 35(10): 2115-2120.
Wang Shaolai, Chen Weiyi, Gu Xuefeng.Adaptive Differential Evolution Algorithms for Multi-Platform Weapon-Target Assignment[J]. Systems Engineering and Electronic Technology, 2013, 35(10): 2115-2120.
[36] 赵明. 多无人机系统的协同目标分配和航迹规划方法研究[D]. 哈尔滨: 哈尔滨工业大学, 2016.
Zhao Ming.Research on Cooperative Target Assignment and Path Planning for Multi-UAV System[D]. Harbin: Harbin University of Technology, 2016.
[37] Storn R, Price K.Differential evolution: a simple and efficient heuristic for global optimization over continuous spaces[J]. Journal Global Optimization (S0925-5001), 1997, 11(4): 341-359.
[38] 雍龙泉. 和声搜索算法研究进展[J]. 计算机系统应用, 2011, 20(7): 244-248.
Yonglongquan. Progress in Harmony Search Algorithms[J]. Computer System Applications, 2011, 20(7): 244-248.
[39] 张媛, 张立民, 刘文彪, 等. 逆转变异蚁群算法在CGF多目标分配[J]. 电光与控制, 2012, 19(3): 21-24.
Zhang Yuan, Zhang Limin, Liu Wenbiao, et al.Reverse Mutation Ant Colony Algorithm in CGF Multi-objective Allocation[J]. Electro-optic and control, 2012, 19(3): 21-24.
[40] 张新. 量子蚁群算法现状综述[J]. 机电一体化, 2014(1): 13-17.
Zhang Xin.A Review of the Status Quo of Quantum Ant Colony Algorithm[J]. Mechatronics, 2014(1): 13-17.
[41] 肖中晖, 寇英信, 李战武, 等. 火力分配多目标优化的IBACO算法[J]. 火力与指挥控制, 2017, 42(7): 165-169.
Xiao Zhonghui, Kou Yingxin, Li Zhanwu, et al.IBACO Algorithm for Multi-objective Optimization of Firepower Allocation[J]. Firepower and command control, 2017, 42(7): 165-169.
[42] 薛洪波, 伦淑娴. 粒子群算法在多目标优化中的应用综述[J]. 渤海大学学报(自然科学版), 2009, 30(3): 265-269.
Xue Hongbo, Lun Shuxian.Summary of the Application of Particle Swarm Optimization in Multi-objective Optimization[J]. Journal of Bohai University (Natural Science Edition), 2009, 30(3): 265-269.
[43] 杨飞, 王青, 候砚泽. 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.
Yang Fei, Wang Qing, Hou Yanze.Multi-platform Weapon Target Allocation based on Improved Particle Swarm Optimization Algorithm in Integer Domain[J]. Journal of Military Engineering, 2011, 32(7): 906-912.
[44] 王强, 丁全心, 张安等. 多机协同对地攻击目标分配算法[J]. 系统工程与电子技术, 2012, 34(7): 1400-1405.
Wang Qiang, Ding Quanxin, Zhang An, et al.Target Allocation Algorithm for Multi-machine Cooperative Ground Attack[J]. Systems Engineering and Electronic Technology, 2012, 34(7): 1400-1405.
[45] 范成礼, 刑清华, 郑明发, 等. 基于IDPSO的武器目标分配优化算法[J]. 系统工程与电子技术, 2015, 37(2): 336-342.
Fan Chengli, Peng Tsinghua, Zheng Mingfa, et al.An IDPSO-based Optimization Algorithm for Weapon Target Allocation[J]. Systems Engineering and Electronic Technology, 2015, 37(2): 336-342.
[46] 夏维, 刘新学, 郑明发, 等. 基于改进型多目标粒子群优化算法的武器-目标分配[J]. 兵工学报, 2016, 37(11): 2085-2093.
Xiawi, Liu Xinxue, Zheng Mingfa, et al. Weapon-Target Assignment based on Improved Multi-objective Particle Swarm Optimization[J]. Journal of Military Engineering, 2016, 37(11): 2085-2093.
[47] 刘志超, 石章松, 姜涛, 等. 基于最小资源损耗的火力分配研究[J]. 火力与指挥控制, 2018, 43(6): 167-170.
Liu Zhichao, Shi Zhangsong, Jiang Tao, et al.Research on Fire Distribution Based on Minimum Resource Loss[J]. Fire and Command Control, 2018, 43(6): 167-170.
[48] Wu F, Zilberstein S, Chen X.Point-based policy generation for decentralized POMDPs[C]. In: Proceeding of AAMAS-10. Toronto, Canada: the 9th International Conference on Autonomous Agents and Multiagent Systems, 2010: 1307-1314.
[49] Wu F, Zilberstein S, Chen X.Trial-based dynamic programming for muti-agent planning[C]. Proceeding of AAMAS-10. Atlanta, USA: the 9th International Conference on Autonomous Agents and Multiagent Systems, 2010: 908-914.
[50] Wu F, Zilberstein S, Chen X.Rollout sampling policy iteration for decentralized POMDPs[C]. Proceeding of UAI-10. Catalina Island, USA: the 9th International Conference on Autonomous Agents and Multiagent Systems, 2010: 666-673.
[51] A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning[J/OL]. [2019-05-28].https://arxiv.org/abs/1711. 00832.