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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 .

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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 http://doi.org/10.3969/j.issn.1001-506X.2014.02.13 <p align="justify">The distributed target assignment of unmanned combat agents (UCA) controlled by manned combat agents (MCA) is very important in MCA/UCA cooperative combat. Under the hypothesis of MCA/UCA hybrid aerial team&rsquo;s architecture and function, the distributed cooperative target assignment model with limited control is established. The integrative model strategy of communication structure, information structure and cooperative mechanism is proposed. Utilizing the contract net protocol as the basic frame, the target selection strategy, announcement strategy, bidding strategy and winner determination strategy of the contract net are extended. Through the improved mechanism of the contract net algorithm, the target can be assigned to UCA and MCA effectively in multiple group. Simulations results based on combat scenario indicate that the algorithm can attain high quality results with low traffic and limited computing time.</p>

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)

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)

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.

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)

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)

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 http://doi.org/10.7527/S1000-6893.2020.24234 To solve the problem of task allocation and cooperative route planning for multiple unmanned aerial vehicles (UAVs), this paper takes the distributed contract network auction algorithm as the basis, designs auction architecture and auction revenue function of UAVs cluster, combines the simulated annealing algorithm to coordinate the task execution order, predicts the range between two task points using the A^* algorithm, completes the initial planning of cooperative route among multiple unmanned aerial vehicles synchronously in the task allocation phase, determines the optimal task execution order, and achieves the tight coupling between the task allocation and cooperative route planning. The simulation results show that, considering the threat of no-fly zones and obstacles, this algorithm can effectively complete the assignment of different targets with reasonable target assignments and execution orders, low total execution cost, and balanced loads among the aircraft. In the stage of task assignment, it has obvious effect to consider cooperative route planning and can effectively improve the rationality of task allocation.

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 http://doi.org/10.12305/j.issn.1001-506X.2024.03.23 针对复杂多任务下的异构无人机(unmanned aerial vehicle, UAV)集群分组调配问题, 提出一种基于改进K均值和延迟接受(deferred-acceptance, DA)算法的先聚类后匹配方法。在任务聚类分组环节, 通过离群点检测和固定初始聚类中心的方法来提高K-means聚类的精度, 并设计余量裕度下的分组均衡性调整策略, 在最优性的前提下提高分组的均衡性。在集群匹配分组环节, 改进了DA算法, 通过任务倾向的偏好列表快速生成预中选方案, 并设计两阶段冲突消除来保证匹配的稳定性和收敛性。仿真实验表明, 所提方法能够快速有效地解决复杂多任务下的UAV集群分组调配问题, 具备良好的最优性和时效性。

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 http://doi.org/10.12305/j.issn.1001-506X.2024.03.23 A method of clustering before matching based on the improved K-means and deferred-acceptance (DA) algorithm is presented to solve the group deployment problem of heterogeneous unmanned aerial vehicle (UAV) swarm for complex multiple tasks. During the task clustering grouping stage, the approach of outlier detection and fixed initial cluster centers is exploited to increase the K-means clustering accuracy, and the grouping equalization adjustment strategy under margin is designed to enhance the grouping equalization based on the optimality condition. In the swarm grouping stage of matching, DA algorithm is developed by the preference list of task preferences to quickly generate a pre-selected scheme, and a two-stage conflict resolution is designed to ensure the matching stability and convergence. The simulation results show that the proposed method can solve the UAV swarm grouping deployment problem for complex multiple tasks quickly and effectively, and possess good optimality and timeliness.

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)

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)

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 http://doi.org/10.3969/j.issn.1000-1093.2021.08.023 An optimization method for the collocation scheme of distributed cooperative operational weapons under different operational conditions is studied based on the comprehensive combat effectiveness and the OODA Loop model. An index system of distributed cooperative operational effectiveness is established, and the underlying operational capability is calculated based on index method. The operational capabilities involved in OODA Loop are analyzed to establish the operational effectiveness evaluation model of every single link. A comprehensive effectiveness evaluation model of the equipment system and an integer programming model for the collocation scheme of weapons are established considering the effectiveness of OODA Loop and its anti-destruction capability. Finally, combining with an example, the optimal collocation scheme of the equipment for performing the reconnaissance mission and the reconnaissance-attacking mission is studied, which proves the feasibility and effectiveness of this method.

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)

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 .

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.

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)

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 .

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 .

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 http://doi.org/10.7527/S1000-6893.2023.28485 针对航空母舰舰载机弹药保障作业高动态、多阶段特性，将柔性流水车间调度方法和群体智能优化理论相结合，提出一种面向舰载机弹药保障作业的调度优化算法。提出将复杂的弹药保障作业调度问题抽象规约为一类考虑工件交货期的柔性流水车间调度问题，引入启发式规则，构建兼顾高效性和可靠性实战要求的弹药保障作业调度数学模型ATSCA。结合弹药保障作业问题特征，设计提出一种基于双层整数编码的贪婪局部搜索遗传算法（GLSGA-DC），改进操作算子和局部搜索算法设计，以最小化弹药保障完成时间为目标对保障模型进行求解。多组仿真结果表明，相比于同类算法，GLSGA-DC算法在Benchmark基准算例和实际弹药转运实例实验中均取得优秀的效果，在求解均值（AVG）、相对偏差（RD）等指标方面均明显占优，验证了ATSCA模型和求解算法在实际弹药保障任务中的有效性和鲁棒性。

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 http://doi.org/10.7527/S1000-6893.2023.28485 Considering the highly dynamic and multi-stage characteristics of carrier-based aircraft ammunition support operations， we establish an optimization model based on the theory of swarm intelligence optimization and the method of flexible flow-shop scheduling. Firstly， the ammunition transfer support operation problem is reduced to a flexible flow-shop scheduling problem considering the delivery time of work-pieces， and heuristic rules are introduced to construct the model of Ammunition Transport Support for Carrier-Borne Aircraft （ATSCA）， which takes into account the requirements of efficiency and robustness. Secondly， combined with the practice of ammunition dispatching operation， a Greedy Local Search Genetic Algorithm with Dual-Level Coding （GLSGA-DC） is designed to solve the ATSCA model with the goal of minimizing the maximum ammunition transfer time. The simulation results show that the GLSGA-DC algorithm has obtained the optimal values in the Mean Value （AVG）， Relative Deviation （RD） and other indicators in benchmark tests and multiple groups of experiments in real ammunition transfer operations， demonstrating the effectiveness and robustness of the ATSCA model and algorithm in real ammunition support operations for carrier-borne aircraft.

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)

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)

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 .

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 http://doi.org/10.12382/bgxb.2024.0212 为提升多无人机协同对地打击任务的作战效能并提高协同任务分配效率,提出一种基于作战单元毁伤概率结果的任务分配方法。构建3种典型地面目标毁伤评估模型,计算不同打击方向下各目标的毁伤概率作为任务分配问题的数据支撑。对各无人机挂载不同武器打击地面目标的典型场景,提出改进混合粒子群优化算法解决任务分配问题。利用遗传算法的交叉、变异操作更新粒子位置,对交叉操作、变异操作进行改进并引入粒子反转操作增加粒子的多样性,避免陷入局部最优。通过仿真算例对所提方法进行验证,结果证明在利用毁伤评估模型计算地面目标的毁伤概率后,所提方法能在满足毁伤要求的前提下得到满足约束条件的任务分配方案,且能提高多无人机体系整体上的作战效能。

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)

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 http://doi.org/10.3969/j.issn.1000-1093.2019.08.022 针对联合火力打击背景下弹药需求预测难的问题，基于武器装备对抗的损失交换比确定不同装备打击不同目标的有效战斗力指数，将有效战斗力指数大小作为衡量敌方目标对我方装备威胁度高低的评判标准，为弹药需求预测提供基本依据。按照对敌最大毁伤原则，建立以最大综合战斗力指数为目标函数的联合火力打击弹药需求预测模型。根据弹药需求量的影响因素设定多种约束条件，结合作战实际及战场态势对约束条件进行随机组合，并运用智能优化算法求解模型。结果表明：该方法合理有效、可操作性强，符合联合火力打击特点，实现了装备-弹药-目标最优编组模式下的弹药需求预测，为未来高技术战争的弹药需求预测开拓了新思路。

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 http://doi.org/10.3969/j.issn.1000-1093.2019.08.022 For the ammunition demand forecast under joint firepower strike, the effective combat effectiveness indexes of different equipment against different targets are determined based on the loss-exchange ratio of weapon-equipment confrontation. The effective combat effectiveness index is taken as a criterion to evaluate the threat of enemy targets to friend equipment, and provide an essential basis for ammunition demand forecasting. According to the principle of maximum damage to enemy, an joint firepower strike ammunition demand forecasting model with the maximum comprehensive combat effectiveness index as the objective function is established. A variety of constraints are set according to the influencing factors of ammunition demand, the constraints are randomly combined according to the actual combat situation, and the intelligent optimization algorithm is used to solve the model. The result shows that the proposed method is reasonable, effective and operable, and represents the characteristics of joint firepower strike. The demand forecasting of joint fire strike ammunition under the optimal equipment-ammunition-target formation mode is realized. Key

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 http://doi.org/10.12382/bgxb.2022.0007 There has been a large number of studies on combat task assignment. However, only a few of them have focused on army force efficiency. This work attempts to address the problem of general combat task assignment from the standpoint of army force utilization. First, the army force is described using single units and compound units in a standardized manner. Second, resource demand analysis is performed and potential resources needed for each task are listed. A mapping relationship is established between the resource and the army force. Then, we formulate the task combination problem and the force dividing code to computational functions mathematically, and introduce the multi-objective optimization method and genetic algorithm to find the optimum task assignment solution. The method is validated using a landing battle example, and the experimental results demonstrate the effectiveness and efficiency of the proposed method.

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)

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 http://doi.org/10.3969/j.issn.1001-506X.2013.02.13 <p align="justify">The manned/unmanned combat Agents task coalition is a new combat mode, which is geared to the needs of the distributed networked operations system. Task allocation is one of the key points in studying the task coalition&rsquo;s command policy. The distributed system architecture adapted to the task coalition is proposed. The task implement quality is introduced into task allocation modeling. Through the improved mechanism of grouping auction as a whole and scheme predisposition, the formed overhead of a unity scheme is reduced. The method rooted in the auction algorithm can realize the dynamic task allocation of the task coalition within the restraint time. Simulation results based on combat scenarios indicate that the algorithm can present the allocation scheme closed to ideal optimal effect in a limited auction cycle.</p>

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YANG Y , LIU D S . A hybrid discrete artificial bee colony algorithm for imaging satellite mission planning [J ] . IEEE Access , 2023 ,11: 40006 - 40017 .

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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. https://doi.org/10.13203/j.whugis20220280. (in Chinese) https://doi.org/10.13203/j.whugis20220280. https://doi.org/10.13203/j.whugis20220280.

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 http://doi.org/10.7527/S1000-6893.2022.27115 针对具有复杂约束的异构多无人机对地目标侦察打击任务分配问题，考虑不确定的任务执行时长、目标消失时间和无人机巡航速度等不确定因素对任务分配结果的影响，基于模糊可信性理论构建以最小化总成本为优化目标的异构多无人机任务分配的模糊机会约束规划模型，并提出一种多策略融合的灰狼优化算法（IMSGWO），通过引入自适应控制参数调整策略、自适应惯性权重策略、最优学习策略与跳出局部最优策略，在增强种群多样性的同时，提高算法的搜索能力。数值分析结果表明：所提算法能够有效求解不确定环境下的异构多无人机任务分配问题。

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 http://doi.org/10.7527/S1000-6893.2022.27115 To solve the problem of task allocation in reconnaissance and attack on ground targets by multi-UAVs with complex constraints， the impact of multiple uncertain factors such as uncertain task execution time， target disappearance time and UAV cruise speed on the task allocation results is considered. A fuzzy chance constrained programming model for multi-UAV task allocation is constructed based on the fuzzy credibility theory， with minimization of the total cost as the optimization goal. In addition， a Multi-Strategy Integrated Grey Wolf Optimization （IMSGWO） algorithm is proposed. By introducing the adaptive control parameter adjustment strategy， adaptive inertia weight strategy， optimal learning strategy and jumping out of local optimal strategy， the search ability of the algorithm is improved while enhancing population diversity. Numerical results show that the proposed algorithm can effectively solve the problem of multi-UAV task allocation in uncertain environment.

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