Collaborative Optimization of Carrier-based Aircraft Task Assignment and Ammunition Configuration

doi:10.12382/bgxb.2024.0461

Abstract

Abstract:

With the escalating complexity of modern naval warfare, the role of carrier-based aircraft in intricate battlefield environments has become increasingly prominent. The collaborative optimization of task assignment and ammunition configuration for carrier-based aircraft is studied to enhance the combat effectiveness and resource utilization efficiency of carrier-based aircraft and alleviate the burden on commanders in formulating the combat plans. The key elements in the collaborative decision-making process are systematically analyzed. Then, an integrated optimization model of carrier-based aircraft task assignment and ammunition configuration is established by taking the maximized mission benefit, minimized destruction cost of carrier-based aircraft and minimized ammunition cost as the optimization objectives. Furthermore, a fitness-based adaptive global artificial bee colony algorithm is developed by combining the characteristics of the model for model solving. The simulated results demonstrate the effectivenesses of the proposed model and algorithm, and that they can significantly improve the mission benefits of carrier-based aircraft while reducing the operational costs. The research results can provide theoretical reference and decision-making basis for the development and improvement of carrier-based aircraft combat plan.

Key words: carrier-based aircraft, task assignment, ammunition configuration, collaborative optimization, evaluation of target significance, artificial bee colony algorithm

CLC Number:

E835.8

GUO Fang, HAN Wei, LIU Jie, SU Xichao, PAN Zishuang. Collaborative Optimization of Carrier-based Aircraft Task Assignment and Ammunition Configuration[J]. Acta Armamentarii, 2025, 46(5): 240461-.

Figures/Tables 16

References 34

[1]	赵启兵, 朱晨帆, 钱帆, 等. 中小型舰载无人机上舰应用发展研究[J]. 兵工自动化, 2023, 42(1):69-75.
	ZHAO Q B, ZHU C F, QIAN F, et al. Research on application development of small and medium-sized shipborne UAVs on ships[J]. Ordnance Industry Automation, 2023, 42(1):69-75. (in Chinese)
[2]	毛晓彬, 梁维泰, 王俊. 空中突击任务分配优化模型研究[J]. 现代防御技术, 2017, 45(5):87-92.
	MAO X B, LIANG W T, WANG J. Optimization model for air strike task assignment[J]. Modern Defence Technology, 2017, 45(5):87-92. (in Chinese)
[3]	万路军, 姚佩阳, 周翔翔, 等. 有人/无人作战智能体分布式协同目标分配方法[J]. 系统工程与电子技术, 2014, 36(2):278-287.
	WAN L J, YAO P Y, ZHOU X X, et al. Distributed cooperative target assignment method of manned combat agents and unmanned combat agents[J]. Systems Engineering and Electronics, 2014, 36(2): 278-287. (in Chinese) doi: 10.3969/j.issn.1001-506X.2014.02.13
[4]	万路军, 姚佩阳, 周翔翔, 等. 多编组协同任务分配模型及DLS-QGA算法求解[J]. 控制与决策, 2014, 29(9):1562-1568.
	WAN L J, YAO P Y, ZHOU X X, et al. Cooperative task allocation methods in multiple groups using DLS-QGA[J]. Control and Decision, 2014, 29(9):1562-1568. (in Chinese)
[5]	姚佩阳, 万路军, 周翔翔, 等. 基于CNDLS的空中多编组时限约束任务分配方法[J]. 空军工程大学学报(自然科学版), 2013, 14(5):21-26.
	YAO P Y, WAN L J, ZHOU X X, et al. Time constraint task allocation methods in multiple aerial group based on circulative nested-dynamic list scheduling[J]. Journal of Air Force Engineering University (Natural Science Edition), 2013, 14(5):21-26. (in Chinese)
[6]	TAN W, HU Y J, ZHAO Y F, et al. Heterogeneous multi UAV mission planning based on ant colony algorithm powered BP neural network[J]. Computational Intelligence and Neuroscience, 2021,2021:4369201.
[7]	吴蔚楠, 关英姿, 郭继峰, 等. 基于SEAD任务特性约束的协同任务分配方法[J]. 控制与决策, 2017, 32(9): 1574-1582.
	WU W N, GUAN Y Z, GUO J F, et al. Research on cooperative task assignment method used to the mission SEAD with real constraints[J]. Control and Decision, 2017, 32(9): 1574-1582. (in Chinese)
[8]	曹严, 龙腾, 孙景亮, 等. 非死锁合同网协议驱动的多机分布式时序任务分配[J]. 宇航学报, 2022, 43(5):675-684.
	CAO Y, LONG T, SUN J L, et al. Multi-UAV distributed task allocation with precedence constraints driven by deadlock-free contract net protocol[J]. Journal of Astronautics, 2022, 43(5):675-684. (in Chinese)
[9]	王然然, 魏文领, 杨铭超, 等. 考虑协同航路规划的多无人机任务分配[J]. 航空学报, 2020, 41(增刊2):724234.
	WANG R R, WEI W L, YANG M C, et al. Task allocation of multiple UAVs considering cooperative route planning[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(S2):724234. (in Chinese) doi: 10.7527/S1000-6893.2020.24234
[10]	高程, 都延丽, 步雨浓, 等. 面向复杂多任务的异构无人机集群分组调配[J]. 系统工程与电子技术, 2024, 46(3):972-981. doi: 10.12305/j.issn.1001-506X.2024.03.23
	GAO C, DU Y L, BU Y N, et al. Heterogeneous UAV swarm grouping deployment for complex multiple tasks[J]. Systems Engineering and Electronics, 2024, 46(3):972-981. (in Chinese) doi: 10.12305/j.issn.1001-506X.2024.03.23
[11]	王峰, 黄子路, 韩孟臣, 等. 基于KnCMPSO算法的异构无人机协同多任务分配[J]. 自动化学报, 2023, 49(2): 399-414.
	WANG F, HUANG Z L, HAN M C, et al. A knee point based coevolution multi-objective particle swarm optimization algorithm for heterogeneous UAV cooperative multi-task allocation[J]. Acta Automatica Sinica, 2023, 49(2): 399-414. (in Chinese)
[12]	邓祁零, 于淼. 基于作战势能的联合火力打击兵力需求测算[C]// 第九届中国指挥控制大会论文集. 北京: 中国指挥与控制学会, 2021.
	DENG Q L, YU M. Calculation of joint fire strike force demand based on operational potential energy[C]// Proceedings of the 9th China Conference on Command and Control. Beijing: Chinese Institute of Command and Control, 2021. (in Chinese)
[13]	陈清霖, 田鸿堂, 王鹏, 等. 基于“OODA”环的分布式协同作战武器编配方案[J]. 兵工学报, 2021, 42(8): 1780-1788.
	CHEN Q L, TIAN H T, WANG P, et al. A Collocation scheme of distributed cooperative operational weapons based on OODA loop[J]. Acta Armamentarii, 2021, 42(8): 1780-1788. (in Chinese) doi: 10.3969/j.issn.1000-1093.2021.08.023
[14]	伏克松. 基于体系结构方法的有人/无人作战体系任务分配研究[D]. 长沙: 国防科技大学, 2019.
	FU K S. Research on task allocation of manned/unmanned combat systems based on architecture method[D]. Changsha: National University of Defense Technology, 2019. (in Chinese)
[15]	ZHANG Y Z, FENG W C, SHI G Q, et al. UAV swarm mission planning in dynamic environment using consensus-based bundle algorithm[J]. Sensors, 2020, 20(8):2307.
[16]	ZHEN Z Y, CHEN Y, WEN L D, et al. An intelligent cooperative mission planning scheme of UAV swarm in uncertain dynamic environment[J]. Aerospace Science and Technology, 2020,100:105826.
[17]	杨惠珍, 王强. 基于动态蚁群劳动分工模型的多AUV任务分配方法[J]. 控制与决策, 2021, 36(8):1911-1919.
	YANG H Z, WANG Q. A multi-AUV dynamic task allocation method based on ant colony labor division model[J]. Control and Decision, 2021, 36(8):1911-1919. (in Chinese)
[18]	GRZEGORZ R, IZABELA N, PAULINA G, et al. Reactive UAV fleet’s mission planning in highly dynamic and unpredictable environments[J]. Sustainability, 2021, 13(9):5228.
[19]	GUO F, HAN W, SU X C, et al. A bi-population immune algorithm for weapon transportation support scheduling problem with pickup and delivery on aircraft carrier deck[J]. Defence Technology, 2023,224:119-134.
[20]	张少辉, 刘舜, 李亚飞, 等. 航空母舰舰载机弹药保障作业调度优化算法[J]. 航空学报, 2023, 44(20):228485. doi: 10.7527/S1000-6893.2023.28485
	ZHANG S H, LIU S, LI Y F, et al. Optimization algorithm for ammunition support operation scheduling of carrier-borne aircraft[J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(20):228485. (in Chinese) doi: 10.7527/S1000-6893.2023.28485
[21]	王丰, 李瑞鹏. 航母航空弹药保障能力优化的可拓策略生成研究[J]. 兵工自动化, 2023, 42(6):8-11.
	WANG F, LI R P. Research on extension strategy generation of aircraft carrier air ammunition support capability optimization[J]. Ordnance Industry Automation, 2023, 42(6):8-11. (in Chinese)
[22]	夏国清, 栾添添, 孙明晓, 等. 舰载机弹药调运不确定系统的T-S模糊优化模型[J]. 控制与决策, 2018, 33(4): 639-643.
	XIA G Q, LUAN T T, SUN M X, et al. T-S fuzzy optimization model for uncertain weapons transporting system in carrier aircraft[J]. Control and Decision, 2018, 33(4): 639-643. (in Chinese)
[23]	YU X Y, GAO X H, WANG L W, et al. Cooperative multi-UAV task assignment in cross-regional joint operations considering ammunition inventory[J]. Drones, 2022, 6(3): 77.
[24]	侯鹏, 葛玉雪, 裴扬, 等. 基于毁伤评估结果的无人机对地攻击任务分配方法[J]. 兵工学报, 2025, 46(2):240212. doi: 10.12382/bgxb.2024.0212
	HOU P, GE Y X, PEI Y, et al. UAV ground attack task assignment method based on damage assessment results[J]. 2025, 46(2):240212. (in Chinese)
[25]	薛辉, 王源, 张天鹏, 等. 随机组合约束下的联合火力打击弹药需求预测模型[J]. 兵工学报, 2019, 40(8): 1716-1724. doi: 10.3969/j.issn.1000-1093.2019.08.022
	XUE H, WANG Y, ZHANG T P, et al. Demand forecasting model for joint fire strike ammunition under stochastic combination constraints[J]. Acta Armamentarii, 2019, 40(8): 1716-1724. (in Chinese) doi: 10.3969/j.issn.1000-1093.2019.08.022
[26]	杜伟伟, 陈小伟. 陆军战术级作战任务分配及优化方法[J]. 兵工学报, 2023, 44(5):1431-1442.
	DU W W, CHEN X W. Task assignment and optimization method of tactical-level army operations[J]. Acta Armamentarii, 2023, 44(5): 1431-1442. (in Chinese) doi: 10.12382/bgxb.2022.0007
[27]	刘学军, 徐洸. 联合火力打击目标毁伤指标分析[J]. 火力与指挥控制, 2004, 44(5):38-40.
	LIU X J, XU G. Research on criterias for target destruction in joint fire strike[J]. Fire Control & Command Control, 2004, 44(5):38-40. (in Chinese)
[28]	万路军, 姚佩阳, 孙鹏. 有人/无人作战智能体分布式任务分配方法[J]. 系统工程与电子技术, 2013, 35(2):310-316.
	WAN L J, YAO P Y, SUN P. Distributed task allocation method of manned/unmanned combat agents[J]. Systems Engineering and Electronics, 2013, 35(2): 310-316. (in Chinese) doi: 10.3969/j.issn.1001-506X.2013.02.13
[29]	LI X D, PENG Y, GUO Y Y, et al. An integrated simulation and AHP-entropy-based NR-TOPSIS method for automated container terminal layout planning[J]. Expert Systems with Applications, 2023,225:120197.
[30]	QI M, TANG J B. Research on psychological health education of higher vocational college students-based on IF-AHP and entropy weight method[J]. Open Journal of Social Sciences, 2024, 12(3):85-95.
[31]	YANG Y, LIU D S. A hybrid discrete artificial bee colony algorithm for imaging satellite mission planning[J]. IEEE Access, 2023,11:40006-40017.
[32]	谢灵惠, 王乐洋, 韩澍豪, 等. 利用GPS观测数据反演震源参数的改进人工蜂群算法[J/OL]. 武汉大学学报(信息科学版), 2022(2022-11-25)[2024-06-29]. https://doi.org/10.13203/j.whugis20220280.
	XIE L H, WANG L Y, HAN S H, et al. An improved artificial bee colony algorithm for inversion of seismic source parameters using GPS observation data[J/OL]. Geomatics and Information Science of Wuhan University, 2022(2022-11-25)[2024-06-29]. https://doi.org/10.13203/j.whugis20220280. (in Chinese)
[33]	张安, 杨咪, 毕文豪, 等. 基于多策略GWO算法的不确定环境下异构多无人机任务分配[J]. 航空学报, 2023, 44(8):327115. doi: 10.7527/S1000-6893.2022.27115
	ZHANG A, YANG M, BI W H, et al. Task allocation of heterogeneous multi-UAVs in uncertain environment based on multi-strategy integrated GWO[J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(8): 327115. (in Chinese) doi: 10.7527/S1000-6893.2022.27115
[34]	SUN K X, ZHENG D Q, SONG H H, et al. Hybrid genetic algorithm with variable neighborhood search for flexible job shop scheduling problem in a machining system[J]. Expert Systems with Applications, 2023,215:119359.

目标毁伤程度	功能丧失程度/%	γ_t/%
目标未毁	0	0
轻度毁伤	0~30	30
中度毁伤	30~60	60
严重毁伤	60~80	80
完全摧毁	80~100	100

目标毁伤程度	功能丧失程度/%	γ_t/%
目标未毁	0	0
轻度毁伤	0~30	30
中度毁伤	30~60	60
严重毁伤	60~80	80
完全摧毁	80~100	100

目标编号	指标1	指标2	指标3	指标4	G_t
1	1	10	6	6	0.296
2	1	10	6	6	0.296
3	4	5	5	4	0.401
4	5	6	5.5	4	0.436
5	4	5	5	4	0.401
6	0.2	2	0.8	1	0.392
7	1	3	2	5	0.156
8	3	7	4	5	0.282
9	2.5	6	5	5.5	0.280
10	2.5	6	5	5.5	0.280
11	0.1	0.1	0.7	0.5	0.415
12	0.3	4	1	3	0.261
13	9	4	11	5	0.630

目标编号	指标1	指标2	指标3	指标4	G_t
1	1	10	6	6	0.296
2	1	10	6	6	0.296
3	4	5	5	4	0.401
4	5	6	5.5	4	0.436
5	4	5	5	4	0.401
6	0.2	2	0.8	1	0.392
7	1	3	2	5	0.156
8	3	7	4	5	0.282
9	2.5	6	5	5.5	0.280
10	2.5	6	5	5.5	0.280
11	0.1	0.1	0.7	0.5	0.415
12	0.3	4	1	3	0.261
13	9	4	11	5	0.630

弹药类型	单位质量	成本
Ⅰ	0.85	0.65
Ⅱ	2.0	1.00
Ⅲ	1.9	0.40
Ⅳ	1.2	0.50
Ⅴ	1.5	0.70