Exact analysis of (R,s, S) inventory control systems with lost sales and zero lead time

We study an (R, s, S) inventory control policy with stochastic demand, lost sales, zero lead‐time and a target service level to be satisfied. The system is modeled as a discrete time Markov chain for which we present a novel approach to derive exact closed‐form solutions for the limiting distribution of the on‐hand inventory level at the end of a review period, given the reorder level (s) and order‐up‐to level (S). We then establish a relationship between the limiting distributions for adjacent values of the reorder point that is used in an efficient recursive algorithm to determine the optimal parameter values of the (R, s, S) replenishment policy. The algorithm is easy to implement and entails less effort than solving the steady‐state equations for the corresponding Markov model. Point‐of‐use hospital inventory systems share the essential characteristics of the inventory system we model, and a case study using real data from such a system shows that with our approach, optimal policies with significant savings in inventory management effort are easily obtained for a large family of items.     

超声速混合层发展情况的非线性时间序列分析

采用大涡模拟数值方法,模拟了具有工程应用背景的二维超声速湍流混合层,通过非线性时间序列分析伪相图、关联维数和Lyapunov指数,得到了混合层发展情况的混沌特性.结果表明,混合层中心线沿流向位置的压力伪相图可定性地表示混合层的稳定性,关联维数分布可定量描述混合层经历的线性失稳、非线性失稳和涡合并阶段等发展情况,最大Lyapunov指数分布作为关联维数分析结果的验证.对于相应的超声速混合层实验,采用非线性时间序列分析方法研究混合层发展情况具有通用性.     

Revenue management under randomly evolving economic conditions

We consider a dynamic pricing model in which the instantaneous rate of the demand arrival process is dependent on not only the current price charged by the concerned firm, but also the present state of the world. While reflecting the current economic condition, the state evolves in a Markovian fashion. This model represents the real‐life situation in which the sales season is relatively long compared to the fast pace at which the outside environment changes. We establish the value of being better informed on the state of the world. When reasonable monotonicity conditions are met, we show that better present economic conditions will lead to higher prices. Our computational study is partially calibrated with real data. It demonstrates that the benefit of heeding varying economic conditions is on par with the value of embracing randomness in the demand process. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 66:73–89,2019     

基于Floyd算法的常规导弹连续波次作战运输规划

为提高常规导弹连续波次作战效能，对常规导弹连续波次作战运输规划问题进行研究。以Floyd算法为基础，首先生成了作战机动区域的交通网络最短路径、距离矩阵；其次将常规导弹连续波次作战运输过程分解为不同阶段，以运输过程中的整体暴露时间最短为目标，构建了初始规划方案0-1整数规划模型；然后考虑道路通行量及地域容量限制，对初始规划方案中存在的地域容量超过限制及单行道路中会车、超车情况进行逐步循环优化，以得到最佳运输规划方案；最后选择了一个作战案例想定，通过Matlab编程对案例进行了求解，得到了针对此案例的最佳运输规划方案，验证了模型的正确性和算法的有效性。     

一体化联合作战指挥决策节点提前工作时间研究

分布式联合决策可缩短系统决策时间,提高决策质量.运用分布式联合决策,其关键点之一是确定各流程节点的工作开始时刻.依据影响分布式联合决策各节点开始工作时刻的主要因素是上下节点间传递的信息的特点,引入了信息熵的概念,通过一定的阈值来确立分布式联合决策系统中各节点的开始决策时刻.利用Bernstein多项式建立了分布式联合决策开始时刻数学模型,给出了求解该数学模型的方法,指出了该模型应用于实践的思路.     

量测误差的时间序列分析方法

针对工程实践中实际量测误差大多并非纯白噪声特点,运用概率统计学的一个分支——时间序列分析中提供的动态数据处理的方法,采用多种的参数估计算法来对量测误差进行拟合和仿真,给出了实验室仿真过程中需叠加的量测误差的新生成办法。所用方法可以推广到对其它数据序列的处理。     

坦克嵌入式车场射击训练炮长操纵控制模型

在嵌入式射击模拟训练系统中,针对炮长操作过程对模拟训练的影响,建立了炮长操纵控制模型。炮长操纵控制模型包括炮长操纵模型和炮长射击决策模型。炮长操纵模型的建立是基于装备的物理模型和人的生理反应模型。炮长射击决策模型根据坦克射击教范要求,采用与/或正向演绎推理得到。在炮长操纵控制模型基础上,建立了射击反应时间模型,并与实际装备操作进行了比较,对建立的操纵控制模型进行了验证。     

基于矩阵运算的光学零件磁流变加工的驻留时间算法

提出了一种光学零件磁流变加工的驻留时间计算方法.该算法以矩阵运算为基础,首先确定工件上各个控制节点的高度余量,并将磁流变抛光模对各控制节点的材料去除能力体现到去除矩阵中,然后利用非负最小二乘法求解驻留时间向量.采用该算法在自行研制的磁流变抛光机床上进行抛光实验,经过2次迭代加工后,有效口径为145mm的球面镜P-V值达到40.5nm(约为λ/15),RMS值达到5nm(约为λ/125),表面粗糙度Ra值达到0.57nm.     

磁流变抛光螺旋扫描方式的算法与实现

研究基于螺旋扫描路径的光学镜面磁流变抛光的算法与实现.该算法将去除函数矩阵转化成驻留时间解算的线性方程组的系数矩阵,并利用其为稀疏矩阵的特点来进行快速迭代计算,然后将求得的驻留时间分配到螺旋扫描路径上以求得整个路径上速度变化,从而控制磁流变抛光机床直线轴和转轴作插补运动.利用该算法在自研的KDMRF-200磁流变抛光机床上对-K9玻璃平面镜进行了两次迭代加工,面形均方根误差由初始的0.128λ加工到0.022λ,验证了该算法的正确性和实用性.     

Scheduling a maintenance activity on parallel identical machines

We study a problem of scheduling a maintenance activity on parallel identical machines, under the assumption that all the machines must be maintained simultaneously. One example for this setting is a situation where the entire system must be stopped for maintenance because of a required electricity shut‐down. The objective is minimum flow‐time. The problem is shown to be NP‐hard, and moreover impossible to approximate unless P = NP. We introduce a pseudo‐polynomial dynamic programming algorithm, and show how to convert it into a bicriteria FPTAS for this problem. We also present an efficient heuristic and a lower bound. Our numerical tests indicate that the heuristic provides in most cases very close‐to‐optimal schedules. © 2008 Wiley Periodicals, Inc. Naval Research Logistics 2009