Resource allocation with lumpy demand: To speed or not to speed?

In the classical EPQ model with continuous and constant demand, holding and setup costs are minimized when the production rate is no larger than the demand rate. However, the situation may change when demand is lumpy. We consider a firm that produces multiple products, each having a unique lumpy demand pattern. The decision involves determining both the lot size for each product and the allocation of resources for production rate improvements among the products. We find that each product's optimal production policy will take on only one of two forms: either continuous production or lot‐for‐lot production. The problem is then formulated as a nonlinear nonsmooth knapsack problem among products determined to be candidates for resource allocation. A heuristic procedure is developed to determine allocation amounts. The procedure decomposes the problem into a mixed integer program and a nonlinear convex resource allocation problem. Numerical tests suggest that the heuristic performs very well on average compared to the optimal solution. Both the model and the heuristic procedure can be extended to allow the company to simultaneously alter both the production rates and the incoming demand lot sizes through quantity discounts. Extensions can also be made to address the case where a single investment increases the production rate of multiple products. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

Properties of some stochastic orders: A unified study

The notions of the likelihood ratio order of degree s (s ≥ 0) are introduced for both continuous and discrete integer‐valued random variables. The new orders for s = 0, 1, and 2 correspond to the likelihood ratio, hazard rate, and mean residual life orders. We obtain some basic properties of the new orders and their up shifted stochastic orders, and derive some closure properties of them. Such a study is meaningful because it throws an important light on the understanding of the properties of the likelihood ratio, hazard rate, and mean residual life orders. On the other hand, the properties of the new orders have potential applications. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

微喷管流动的DSMC方法模拟

目前微型航天器正在积极地发展中,微喷管在其推进系统中具有重要地位,对微喷管进行进一步研究是很有必要的。运用DSMC(DirectSimulationMonte Carlo)方法从分子运动论层次对轴对称微喷管流动现象进行模拟,分析了喷管流量以及尺寸大小对喷管流动和性能的影响。研究表明,喷管流量及尺寸对流动特性和微喷管性能存在不同程度的影响。     

基于角速率输入的圆锥误差补偿算法

针对光纤陀螺姿态测量系统中利用角速率拟合角增量进行圆锥误差补偿精度下降的问题,在陀螺仪角速率输入下,采用参数解析法优化的三子样算法,直接利用陀螺的角速率输出进行圆锥误差补偿。同时考虑工程实际中滤波器的影响,推导滤波角速率输入下三子样误差补偿算法的具体表达形式。仿真分析表明：参数解析法优化的角速率输入圆锥误差补偿算法优于传统算法;而针对滤波器引入的不可忽略的算法误差,可通过修正圆锥算法系数进行补偿。     

基于饱和度梯度的彩色序列图像光流场计算

传统的基于亮度守恒的光流法仅利用图像灰度信息进行光流求解,忽略了对包含丰富信息的色彩信息的利用。而彩色光流法虽然利用了彩色图像各通道信息,却忽略了对邻域信息的利用,造成存在各通道线性相关而无法求解的问题。同时,上述方法在光照变化时均不能得到正确的光流场估计。将基于饱和度的梯度计算方法引入灰度光流的计算方法中,提出了基于饱和度梯度的彩色光流计算方法,该方法有效地利用了彩色图像的色彩信息和邻域信息。试验结果证明：该方法提高了算法对光照变化的适应性,得到了更加精确的光流场估计,且避免了各通道线性相关的问题,为运动目标检测奠定了基础。     

激光加热辅助引弧微爆炸加工工程陶瓷的试验研究

为验证激光加热辅助技术改善引弧微爆炸加工质量和提高加工效率的可行性,探索加工工艺参数对加工过程的影响规律,设计了激光加热辅助引弧微爆炸加工试验系统,并通过试验研究了工艺参数对材料去除率和崩碎的影响规律。试验结果表明：激光加热辅助引弧微爆炸加工陶瓷可以提高材料去除率,改善崩碎情况;加工效率随激光功率的增加而提高,随光斑尺寸的增大而降低,随距离的增加先提高后降低;崩碎随激光功率的增加而减少,随光斑尺寸的增大先减少后增多,随距离的增加先减少后增多。研究结果为激光加热辅助引弧微爆炸加工机理的研究和工艺参数的优化提供了参考依据。     

转速对动态旋流器流场影响的数值分析

根据计算流体力学方法,对采用不同转速的动态旋流器流场进行数值模拟,深入分析了转速对动态旋流器切向速度、静压以及湍动能的影响。计算采用雷诺应力模型和混合物模型。结果表明:转速对动态旋流器切向速度和静压影响非常大,不但影响其数值大小,对其分布趋势也产生明显影响;转速对动态旋流器湍动能的影响主要集中在旋转栅附近,在转筒后半段转速对湍动能的影响明显弱化,适当提高转速甚至有抑制湍流的作用。     

平行度动态测量的新方法

平行度测量是舰船设备系统标校的前提,传统的平行度测量方法需要依赖"星"或"标"的配合,由于舰船所在位置的限制,可能不具备设置"星"或"标"的条件,利用夜空的星星也很受限。为克服环境条件对标校的限制,可以采用角速率陀螺作为传感器动态测量指向设备的平行度,推出了计算俯仰和旋回零位误差的公式,并对器件误差的影响进行了估算,计算结果说明现有的角速率陀螺器件的精度能满足本测量方法的需求。该研究成果可在舰船设备系统标校中运用,以克服传统方法依赖外界条件的难题。     

Evaluating cost and reliability integrated performance of stochastic logistics systems

The significance of integrating reliability into logistics performance has been established [The Logistics Performance Index and Its Indicators, World Bank International Trade and Transport Departments, (2010)]. Hence, as a response to the work by the World Bank, the present article aims to evaluate the performance index R_b,d of logistics systems as the probability that a specified demand d can be distributed successfully through multistate arc capacities from the source to the destination under the constraint that the total distribution cost should not exceed the cost limitation b. This article provides a pioneering approach for a straightforward computation of the performance index R_b,d. The proposed algorithm is a hybrid between the polynomial time capacity‐scaling algorithm, which was presented by Edmonds and Karp [JACM 19 (1972)], and the decomposition algorithm, which was presented by Jane and Laih [IEEE (2008)]. Currently, the proposed approach is the only algorithm that can directly compute R_b,d. An illustration of the proposed algorithm is presented. The results of the computational experiments indicate that the presented algorithm outperforms existing algorithms. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Stein–Chen approximation and error bounds for order fill rates in assemble‐to‐order systems

Assemble‐to‐order (ATO) is an important operational strategy for manufacturing firms to achieve quick response to customer orders while keeping low finished good inventories. This strategy has been successfully used not only by manufacturers (e.g., Dell, IBM) but also by retailers (e.g., Amazon.com). The evaluation of order‐based performance is known to be an important but difficult task, and the existing literature has been mainly focused on stochastic comparison to obtain performance bounds. In this article, we develop an extremely simple Stein–Chen approximation as well as its error‐bound for order‐based fill rate for a multiproduct multicomponent ATO system with random leadtimes to replenish components. This approximation gives an expression for order‐based fill rate in terms of component‐based fill rates. The approximation has the property that the higher the component replenishment leadtime variability, the smaller the error bound. The result allows an operations manager to analyze the improvement in order‐based fill rates when the base‐stock level for any component changes. Numerical studies demonstrate that the approximation performs well, especially when the demand processes of different components are highly correlated; when the components have high base‐stock levels; or when the component replenishment leadtimes have high variability. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012