Game-theoretic modeling and control of a military air operation

An attrition-type discrete-time dynamic model is formulated for two opposing forces, labeled Blue and Red, engaged in a military air operation. The Blue force consists of combat air units and its objective is to destroy a fixed target, such as an airport or a bridge, which Is being defended by the Red force. The Red force consists of ground troops and air defense units. We model the objective functions for each side and identify the associated constraints on the control and state variables. We employ a two-level hierarchy of command and control for each force. An example scenario illustrating the implementation of this approach using concepts from non-zero sum dynamic game theory is presented     

动态保障结构下多级多层备件配置优化建模

针对作战编队执行长时间、远距离任务期间,编队后方保障站点变更的情况,结合部队维修保障的特点,基于可修复备件多级管理(METRIC)理论,通过计算编队剩余备件分布规律,建立了动态保障体系结构下基于时变可用度的三级两层备件保障模型。以备件储存空间为约束,可用度为目标,建立了分阶段边际优化模型。列举实例,采用分阶段边际算法对备件方案进行优化,对比分析了动态保障结构下和固定保障结构下装备可用度随时间的变化,并采用蒙特卡罗仿真方法对案例进行实验验证。案例结果表明:采取多个后方站点的保障方式能有效提高装备可用度;案例仿真实验结果与解析结果误差在4%以内。模型可为保障决策者制定备件方案提供辅助决策工具。     

Decentralized algorithms for netcentric force protection against antiship missiles

We model a decentralized network of decision makers charged with optimally deploying hardkill and/or softkill weapons (countermeasures (CMs)) to defend a task group from antiship missiles. Each platform (decision maker) observes missile threats using a combination of shipboard sensor measurement data and data from other ships, but acts independently when controlling its own weapon systems to cooperatively pursue the defensive objectives of the task group in a decentralized fashion. The main results are a formulation of the missile deflection problem as a stochastic shortest path Markovian game with constraints, a characterization of the Nash equilibrium solution, and a decentralized algorithm for computing the Nash equilibrium when the stochastic game is collaborative. Numerical examples are given to demonstrate the equilibrium policies and illustrate their sensitivity to the missile dynamics.     

Linear-quadratic and norm-bounded differential game combined guidance strategy against active defense aircraft in three-player engagement

A new type of guidance strategy, combining linear quadratic and norm-bounded game theory, is proposed for the scenario of an attacker against active defense aircraft in three-player engagement. The problem involves three players, an attacker, a defender and a target. The differential game theory and the solution of Hamiltonian equation are utilized to obtain the combined guidance strategy for each player with arbitrary-order dynamics. The game process is divided into 4 phases, C1-C4, according to the switching time. The linear quadratic differential game guidance scheme is employed to reduce the fuel cost in the game parts of C1 and C3. The norm-bounded game guidance strategy is adopted to satisfy the constraint of control input in the game stages C2 and C4. Furthermore, zero-effort miss distance is introduced to meet the constraints of game space and defender’s killing radius in the guidance strategy, which guarantees that the attacker is able to avoid the interception of the defender and hit the target with lower fuel cost and maximum acceleration. And it is proved that the proposed guidance strategy satisfies the Nash equilibrium condition. Finally, the feasibility and superiority of combined guidance strategy are respectively illustrated by nonlinear numerical simulation and verified by comparing with linear quadratic and norm-bounded differential game guidance strategies.     

中国民航运输业缝隙市场竞争博弈分析

基于缝隙市场理论和博弈理论，新建了缝隙市场竞争博弈模型，分析了中国民航运输业在规制放松过程中不同市场结构下新航空公司和原在位航空公司之间的市场竞争行为，证明了新航空公司运用缝隙市场竞争策略既可以较大可能地避免在位者的挤压，也能最大程度地获得规制者的优先容纳。缝隙市场竞争策略是新进入者参与市场博弈的占优策略。     

基于微分对策的临近空间飞行器机动突防策略

针对飞行器机动突防问题,基于微分对策理论对飞行器在攻防对抗中制导阶段的机动突防策略进行设计与分析。首先将攻防对抗问题转化为二人零和博弈问题,并设计了二次型目标函数;其次,考虑到飞行器计算能力不足的问题,采取了适当假设以得到博弈问题的解析解,便于实际应用;最后对该机动突防策略进行了仿真验证,结果表明在攻防对抗中制导阶段,飞行器采用微分对策制导律,相较于正弦机动不仅减少自身54.3%的能量消耗,而且增加了拦截器58.6%的能量消耗,将显著增加飞行器末制导段对抗突防能力。     

军工企业管理的自组织方法论

运用自组织理论,分析了自组织系统的特征及我国军工企业的现状,提出了军工企业管理系统所要遵循的四种管理方法和思想。     

军工企业推行项目管理的几点思考

在分析军工企业项目管理特征和发展简史的基础上,结合相关理论和笔者从事项目管理的工作实践,对现行体制下我国军工企业推行项目管理提出了若干思考意见和工作建议。     

Pop-up threat models for persistent area denial

Pop-up threats usually appear or disappear randomly in a battle field. If the next pop-up threat locations could be predicted it would assist a search or attack team, such as in a persistent area denial (PAD) mission, in getting a team of unmanned air vehicles (UAVs) to the threats sooner. We present a Markov model for predicting pop-up ground threats in military operations. We first introduce a general Markov chain of order n to capture the dependence of the appearance of pop-up threats at previous locations of the pop-up threats over time. We then present an adaptive approach to estimate the stationary transition probabilities of the nth order Markov models. To choose the order of the Markov chain model for a specific application, we suggest using hypothesis tests from statistical inference on historical data of pop-up threat locations. Anticipating intelligent responses from an adversary, which might change its pop-up threat deployment strategy upon observing UAV movements, we present adaptive Markov chain models using a moving horizon approach to estimate possibly abrupt changes in transition probabilities. We combine predicted and actual pop-up target locations to develop efficient cooperative strategies for networked UAVs. A theoretical analysis and simulation results are presented to evaluate the Markov model used for predicting pop-up threats. These results demonstrate the effectiveness of cooperative strategies using the combined information of threats and predicted threats in improving overall mission performance.     

中层干部执行力对民机事业的影响

中国民机事业的发展离不开一支优秀的员工队伍,其中中层干部是这支优秀队伍的中坚力量和业务骨干。在企业日常管理中,他们既是执行者又是决策者,不仅要做好桥梁纽带作用,更要为如何执行企业战略目标负责。中层干部执行力的强弱,很大程度上反映了一个企业绩效管理水平的高低。结合实际工作,从执行力的定义、作用、强化中层干部执行力的意义、中层干部在执行力上存在的问题、提高中层干部执行力的方法和中层干部提升执行力的要素等方面谈谈自己的看法。     

现代空战机动决策研究

将影响图和对策论引入到现代空战机动决策中,提出了考虑交战双方对抗的n步连续机动决策的多级影响网对策决策模型。首先,确定现代空战飞机相关数学和运动模型;其次,将大规模群集空战转化为多个小集团作战;在此基础上,依据协同的原则,又将小集团作战转化为多个一对一空战,然后运用多级影响图对策理论解决一对一空战。空战仿真结果表明该模型的有效性。     

基于博弈论的自由空战指挥引导对策问题研究

博弈论是解决空战对抗问题的有效方法之一,针对目前自由空战筹划困难、指挥引导对策单一的现状,在现有空战博弈问题研究的基础上,扩展了机动动作库和控制参数,加入了雷达开机时机这一关键决策,分别从静态博弈和动态博弈角度出发,提出了构建自由空战指挥引导对策模型的思路,为下一步指挥引导对策模型的研究奠定了基础.     

基于改进匈牙利算法的航空企业动态调度方法研究

航空零件生产调度时,应尽量满足多目标和实时性的要求。结合某航空制造企业的实际生产情况,提出一种基于"穷尽成对比较"技术和改进匈牙利算法的动态调度方法。首先以航空零件调度时的最大完工时间、生产加工成本以及生产能耗为优化目标,构建柔性作业车间多目标动态调度数学模型;然后利用基于"穷尽成对比较"技术的权重参数调节模型对数学模型中各个目标的权重参数进行实时动态调整;最后以各个目标的加权值为总目标,采用改进匈牙利算法求得工序的最优分配结果。结果表明:与传统的动态调度方法相比,动态调度方法能够有效地提高航空企业的生产效率、减少航空企业的生产加工成本并降低对环境的污染,具有较好的综合调度性能。     

非对称机动能力多无人机智能协同攻防对抗

协同攻防对抗是未来军用无人机的重要作战场景。针对不同机动能力无人机群体间的攻防对抗问题，建立了多无人机协同攻防演化模型，基于多智能体强化学习理论，研究了多无人机协同攻防的自主决策方法，提出了基于执行-评判（Actor-Critic）算法的集中式评判和分布式执行的算法结构，保证算法稳定收敛的同时，提升执行效率。无人机的评判模块使用全局信息评价决策优劣引导策略学习，而执行时只需要依赖局部感知信息进行自主决策，提高了多机攻防对抗的效能。仿真结果表明，所提的多无人机强化学习方法具备较强的自进化属性，赋予了无人机一定智能，即稳定的自主学习能力，通过不断演化，能自主学习提升协同对抗的决策效能。     

舰载机智能复飞决策技术研究

为了进一步改进复飞技术,针对复飞环境,提出了一种在原军用推力操纵的基础上,加入具有保持迎角恒定的升降舵模糊控制的复飞系统,从而有效地增强了低动压状态下飞机的机动能力。给出了复飞决策准则,设计了基于模糊控制的复飞决策系统,并对具有该复飞决策系统的舰载机自动着舰导引系统进行了仿真验证。结果表明,该复飞决策系统明显地缩小了复飞边界区,大大提高了着舰和复飞的安全性,可实现自动复飞,减轻了飞行员的负担。     

耦合均衡论和隐式约束伴随方法的翼型气动多目标优化设计

通过耦合Nash竞争对策和伴随方法来研究气动多目标优化问题,其中对策论是描述现实世界中包含有矛盾、冲突、对抗、合作等诸因素的数学模型的数学理论与方法。将对策论的方法应用于互为冲突的多目标气动优化设计中,寻找各冲突目标之间的平衡解。计算结果表明：Nash均衡论可以很好地处理多目标优化问题,并且能自然地运用于并行环境。     

实物期权理论在企业投资决策中的优势

文章介绍了实物期权理论的基本概念以及与传统投资决策方法的比较优势,以期推动实物期权理论在不确定条件下的决策应用,使得企业在投资决策上更具科学性和合理性.     

自主空战机动决策方法综述

自主空战机动决策是基于数学优化、人工智能等方法,模拟飞行员空战决策,自动生成飞行控制指令的过程。它在空战仿真、飞行员辅助决策和无人战斗机自主飞行等领域广泛运用。根据求解思路的不同,综合论述了两类自主空战机动决策方法:针对基于对策的空战决策方法,阐述了从追逃对策到双目标对策的发展脉络和内在联系,并着重分析了两类重要的双目标对策模型——矩阵对策和影响图对策;针对基于人工智能的空战决策方法,系统论述了基于专家系统的机动决策、基于遗传学习系统的机动决策、基于人工免疫系统的机动决策和基于神经网络的机动决策,明确了各种决策的建模方法、适用条件、改进途径等问题。总结了各个空战机动决策方法的优点及不足,指出了自主空战机动决策的进一步研究思路。     

基于分支深度强化学习的非合作目标追逃博弈策略求解

为解决航天器与非合作目标的空间交会问题,缓解深度强化学习在连续空间的应用限制,提出了一种基于分支深度强化学习的追逃博弈算法,以获得与非合作目标的空间交会策略。对于非合作目标的空间交会最优控制,运用微分对策描述为连续推力作用下的追逃博弈问题;为避免传统深度强化学习应对连续空间存在维数灾难问题,通过构建模糊推理模型来表征连续空间,提出了一种具有多组并行神经网络和共享决策模块的分支深度强化学习架构。实现了最优控制与博弈论的结合,有效解决了微分对策模型高度非线性且难于利用经典最优控制理论进行求解的难题,进一步提升了深度强化学习对离散行为的学习能力,并通过算例仿真检验了该算法的有效性。     

An Application of Evidential Networks to Threat Assessment

Decision makers operating in modern defence theatres need to comprehend and reason with huge quantities of potentially uncertain and imprecise data in a timely fashion. An automatic information fusion system is developed which aims at supporting a commander's decision making by providing a threat assessment, that is an estimate of the extent to which an enemy platform poses a threat based on evidence about its intent and capability. Threat is modelled by a network of entities and relationships between them, while the uncertainties in the relationships are represented by belief functions as defined in the theory of evidence. To support the implementation of the threat assessment functionality, an efficient valuation-based reasoning scheme, referred to as an evidential network, is developed. To reduce computational overheads, the scheme performs local computations in the network by applying an inward propagation algorithm to the underlying binary join tree. This allows the dynamic nature of the external evidence, which drives the evidential network, to be taken into account by recomputing only the affected paths in the binary join tree.