Dynamic learning,pricing, and ordering by a censored newsvendor

We address the problem of determining optimal ordering and pricing policies in a finite‐horizon newsvendor model with unobservable lost sales. The demand distribution is price‐dependent and involves unknown parameters. We consider both the cases of perishable and nonperishable inventory. A very general class of demand functions is studied in this paper. We derive the optimal ordering and pricing policies as unique functions of the stocking factor (which is a linear transformation of the safety factor). An important expression is obtained for the marginal expected value of information. As a consequence, we show when lost sales are unobservable, with perishable inventory the optimal stocking factor is always at least as large as the one given by the single‐period model; however, if inventory is nonperishable, this result holds only under a strong condition. This expression also helps to explain why the optimal stocking factor of a period may not increase with the length of the problem. We compare this behavior with that of a full information model. We further examine the implications of the results to the special cases when demand uncertainty is described by additive and multiplicative models. For the additive case, we show that if demand is censored, the optimal policy is to order more as well as charge higher retail prices when compared to the policies in the single‐period model and the full information model. We also compare the optimal and myopic policies for the additive and multiplicative models. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

战时运输道路决策支持模型

战时与平时道路问题比较,最为显著的特点就是敌情对道路的制约作用。战时道路问题是一个多因素、多目标决策问题。解决该问题的思路是:首先穷举可能方案,然后计算每个方案各步骤的目标值,再将各步骤目标值综合成方案的目标值,最后进行方案的排劣、优选,得到适当数量的(3～5个)方案供决策者使用。决策目标有:完成运输的时间、货物损失率和不能完成运输任务的概率。     

新型小规模装备备件品种确定的犹豫模糊粗糙集决策方法

针对新研装备备件品种确定过程中决策信息“犹豫性”和“模糊性”特点突出、难以运用传统备件品种确定方法进行决策的问题,提出一种基于犹豫模糊粗糙集的备件品种确定方法。利用风险偏好系数对不完备犹豫模糊信息进行数值延拓,为构建不同风险偏好下备件品种确定的犹豫模糊决策信息系统奠定了基础；考虑得分函数和数值延拓边界的综合因素影响给出了改进的包含度计算公式,并基于包含度定义进行了证明；给出了基于改进包含度计算的备件品种决策属性的约简条件和规则获取方法,实现了犹豫模糊决策信息的深度挖掘和有效利用。以某新研装备备件品种确定为例进行了方法验证,研究结果表明：通过该法能够有效处理犹豫模糊决策信息,获取精简实用的备件品种决策规则集,验证了方法的可行性。     

反舰导弹攻击三位一体图形化战术决策

反舰导弹攻击三位一体图形化战术决策,是将反舰导弹攻击时的捕捉概率决策、火分目标决策、航路规划决策等三种决策合为一体,以图形化的操作界面作为主要的决策交互手段,通过对各种图形的操作达到战术决策的目的。重点分析和研究了反舰导弹攻击三位一体图形化战术决策的基本思路、决策过程、设计原则、作战流程和图形设计,对开展反舰导弹攻击战术决策软件的研制具有一定的理论参考价值。     

Dynamic service rate control for a single‐server queue with Markov‐modulated arrivals

We consider the problem of service rate control of a single‐server queueing system with a finite‐state Markov‐modulated Poisson arrival process. We show that the optimal service rate is nondecreasing in the number of customers in the system; higher congestion levels warrant higher service rates. On the contrary, however, we show that the optimal service rate is not necessarily monotone in the current arrival rate. If the modulating process satisfies a stochastic monotonicity property, the monotonicity is recovered. We examine several heuristics and show where heuristics are reasonable substitutes for the optimal control. None of the heuristics perform well in all the regimes and the fluctuation rate of the modulating process plays an important role in deciding the right heuristic. Second, we discuss when the Markov‐modulated Poisson process with service rate control can act as a heuristic itself to approximate the control of a system with a periodic nonhomogeneous Poisson arrival process. Not only is the current model of interest in the control of Internet or mobile networks with bursty traffic, but it is also useful in providing a tractable alternative for the control of service centers with nonstationary arrival rates. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 60: 661–677, 2013     

多传感器目标识别和火力分配群决策算法

针对多传感器目标识别的群决策问题,考虑到多目标威胁程度评价指标属性的模糊性,首先将多传感器目标评价属性的定量、定性描述指标统一转化为三角模糊数,充分利用三角模糊数性质构建群决策函数,实现定量指标与定性指标的规范化处理,在此基础上提出一种基于加权矩阵排序的三角模糊数多传感器目标识别的群决策算法,实现对多传感器目标的威胁程度的综合评估.最后,通过多传感器目标评估实例分析并证明了算法的可行性和有效性.同时实验发现该算法对于多属性、多评价者的群体决策具有优势,且不易受外界参数变化的影响.     

一种鲁棒的场地球类视频中的球门探测方法

在场地球类视频中,球门常常会伴随着精彩片段而出现。因此,球门探测是体育视频的基础,同时也是视频高层语义概念探测的研究热点。目前,利用机器学习方法进行视频中的对象探测是非常有前途的研究领域。基于此,提出一种基于模糊决策树的球门探测算法,用来探测场地球类视频中球门帧的出现,为了提高分类准确性,在模糊决策树训练的过程中加入了平衡处理。实验结果表明,与基于阈值和决策树的算法相比,该算法可以得到更好的分类结果(F-measure>95%),并且我们可以从所建立的树中推导出模糊规则来解释分类模型。     

基于粗糙集-神经网络编队协同空战决策系统

为了提高空战决策的实时性和准确度,将粗糙集理论和神经网络引入到编队协同空战战术决策研究中,提出了应用SOM网络-粗糙集-BP网络集成进行编队协同空战战术决策的方案:应用SOM网络离散化决策系统输入数据的连续属性值;利用粗糙集数据分析方法,从数据中提取出规则将输入映射到输出的子空间上;在这个子空间上用BP网络进行逼近.2:4编队空战实例仿真结果验证该方案的可行性,在数据充分的条件下,该方案可以推广应用于其它空战决策系统.     

多指标下的炮兵火力最优分配

为了提高炮兵火力打击效能,提出了小生境遗传算法与模糊多目标决策相结合的混合算法,建立了多指标下的炮兵火力分配模型,并阐述了混合算法设计,给出了应用举例,结果表明,与传统的单指标下的炮兵火力最优分配相比,该方法更符合战场实际情况。     

基于向量皮尔森相关系数的组合赋权法

针对多属性决策中属性权重的确定问题,提出了一种基于皮尔森相关系数的主、客观权重的集成方法。用权向量的相关度作为不同赋权方法重要性的度量,意义明确,计算简单,可操作性强。最后采用算例验证了此方法的有效性和实用性。