DEA models for two‐stage processes: Game approach and efficiency decomposition

Data envelopment analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs). This tool has been utilized by a number of authors to examine two‐stage processes, where all the outputs from the first stage are the only inputs to the second stage. The current article examines and extends these models using game theory concepts. The resulting models are linear, and imply an efficiency decomposition where the overall efficiency of the two‐stage process is a product of the efficiencies of the two individual stages. When there is only one intermediate measure connecting the two stages, both the noncooperative and centralized models yield the same results as applying the standard DEA model to the two stages separately. As a result, the efficiency decomposition is unique. While the noncooperative approach yields a unique efficiency decomposition under multiple intermediate measures, the centralized approach is likely to yield multiple decompositions. Models are developed to test whether the efficiency decomposition arising from the centralized approach is unique. The relations among the noncooperative, centralized, and standard DEA approaches are investigated. Two real world data sets and a randomly generated data set are used to demonstrate the models and verify our findings. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

相控阵雷达维修方案优选方法研究

针对相控阵雷达维修方案的选择问题,确定了维修方案的决策属性,并提出一种基于改进TOPSIS法的相控阵雷达维修方案优选方法。该方法通过引入Vague集来处理维修方案选择中存在的模糊信息,并采用博弈论综合赋权法来确定决策属性的综合权重。通过计算各备选方案与正、负理想方案的灰色关联度,得到了维修方案的灰色关联相对贴近度,进而实现对维修方案的排序和选择。最后,通过算例应用与分析,对提出的方法进行了验证。     

基于多项式设计法的小推力轨迹设计

形状逼近法是小推力轨迹设计中的一种有效方法,然而现有的方法大都假定运动轨迹为某一特定的形状,而且没有考虑推力加速度的约束限制。针对小推力轨道交会问题,提出一种基于多项式的轨迹设计方法。结合极坐标系,建立基于多项式的三自由度轨迹运动模型,将轨迹设计问题转化为求解多项式的系数问题;根据运动模型推导轨迹的动力学特性,建立约束方程,并以消耗燃料最少作为性能指标,采用序列二次规划的方法对多项式的系数进行寻优计算。该方法不仅能求解多个形状设计参数不确定性问题,而且还能满足推力加速度的约束限制。仿真验证了该方法的正确性和可用性,该方法可为任务设计初步阶段的轨迹设计和燃料消耗预估提供一定的技术参考。     

Potential impact of recharging plug‐in hybrid electric vehicles on locational marginal prices

Plug‐in hybrid electric vehicles (PHEVs), upon market penetration, will create additional recharging loads to the electric power systems. This article considers different recharging scenarios and uses game theoretic models to study the potential impact of the recharging loads on locational marginal prices (wholesale electricity prices). Computational results from a Pennsylvania‐New Jersey‐Maryland Interconnection case study show that, under the existing recharging infrastructures, even a small magnitude of load increase caused by PHEV recharging could have a significant undesirable impact on locational marginal prices. The impact could be mitigated to a varying extent by the availability of possible future recharging infrastructures, including realtime pricing recharging meters, battery stations, or vehicle‐to‐grid technology.© 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

基于模糊双矩阵对策的作战效能评估模型

讨论了策略集清晰、支付值模糊的模糊双矩阵对策的一种求解方法,并以某型导弹混编群对抗ARM（反辐射导弹）及载机为案例进行研究,建立了基于模糊双矩阵对策的作战效能评估模型,研究结果对于双方资源分配,提高作战效能具有一定的军事应用价值。     

给定极小样本量的定量截尾序贯检验法及其应用

对现有截尾序贯检验法作了必要的改进,提出定量截尾序贯检验法。结合导弹命中精度验收试验的工程实际需求,在事先给定几种特小样本量的前提下,针对定量截尾序贯检验法的实际应用展开研究,给出了可应用于实际的检验方案。通过对检验实例的比较分析,说明了方案的优越性。     

微分对策及其在军事领域的研究进展*

介绍了微分对策的产生背景及其半个多世纪以来的发展历程,简述了国内外微分对策理论发展的几个重要阶段及其标志性成果。全面地阐述了国内外关于微分对策在军事领域的应用研究状况,特别是美、俄等军事强国在微分对策军事应用研究方面的现状以及我国研究人员在该领域的主要研究成果。还进一步论述了微分对策在军事应用研究方面存在的问题,并对微分对策的发展前景做出了展望,指出了微分对策在军事应用领域中的研究热点、难点和主要发展方向。     

联合作战的远程火力战法动态分析方法*

用定量动态分析方法开发远程火力战法是联合作战规划中必须解决的重要问题。借助仿真和博弈分析的混合方法,在对博弈效用函数计算的基础上,构建基于识别真目标、假目标以及火力命中目标概率的二人非零和(TPNZS)非合作博弈模型来开发远程火力战法动态分析方法,对两个典型的联合作战远程火力打击战法性能的初步动态分析表明:战场势态的动态变化直接影响定量规划最优战法的结果。     

A sequential partial information bomber-defender shooting problem

A bomber carrying homogenous weapons sequentially engages ground targets capable of retaliation. Upon reaching a target, the bomber may fire a weapon at it. If the target survives the direct fire, it can either return fire or choose to hold fire (play dead). If the former occurs, the bomber is immediately made aware that the target is alive. If no return fire is seen, the true status of the target is unknown to the bomber. After the current engagement, the bomber, if still alive, can either re-engage the same target or move on to the next target in the sequence. The bomber seeks to maximize the expected cumulative damage it can inflict on the targets. We solve the perfect and partial information problems, where a target always fires back and sometimes fires back respectively using stochastic dynamic programming. The perfect information scenario yields an appealing threshold based bombing policy. Indeed, the marginal future reward is the threshold at which the control policy switches and furthermore, the threshold is monotonic decreasing with the number of weapons left with the bomber and monotonic nondecreasing with the number of targets left in the mission. For the partial information scenario, we show via a counterexample that the marginal future reward is not the threshold at which the control switches. In light of the negative result, we provide an appealing threshold based heuristic instead. Finally, we address the partial information game, where the target can choose to fire back and establish the Nash equilibrium strategies for a representative two target scenario.     

游戏：走向教学对话的本真

教学对话是教师、学生与文本之间实现的智识共享、双向理解和意义创生,达成多重视界的融合。教学中教师的独白、预设的问答以及片面的对话向我们展现的是遮蔽的教学对话。游戏与教学对话有着某种契合,游戏与教学对话的相融,教师、学生和文本之间达成智识共享、共同在场、意义的创生、全面的对话直至多重的视界相融,使教学对话真正走向本真之境。