Designing a degradation experiment

Degradation experiments are widely used to assess the reliability of highly reliable products which are not likely to fail under the traditional life tests. In order to conduct a degradation experiment efficiently, several factors, such as the inspection frequency, the sample size, and the termination time, need to be considered carefully. These factors not only affect the experimental cost, but also affect the precision of the estimate of a product's lifetime. In this paper, we deal with the optimal design of a degradation experiment. Under the constraint that the total experimental cost does not exceed a predetermined budget, the optimal decision variables are solved by minimizing the variance of the estimated 100pth percentile of the lifetime distribution of the product. An example is provided to illustrate the proposed method. Finally, a simulation study is conducted to investigate the robustness of this proposed method. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 689–706, 1999     

Algorithms for computing waiting time distributions under different queue disciplines for the D-BMAP/PH/1

A queueing system characterized by the discrete batch Markovian arrival process (D-BMAP) and a probability of phase type distribution for the service time is one that arises frequently in the area of telecommunications. Under this arrival process and service time distribution we derive the waiting time distribution for three queue disciplines: first in first out (FIFO), last in first out (LIFO), and service in random order (SIRO). We also outline efficient algorithmic procedures for computing the waiting time distributions under each discipline. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 559–576, 1997     

Single machine sequencing with linear models of release dates

The paper deals with a problem of scheduling a set of jobs on a single machine. Before a job is released for processing, it must undergo some preprocessing treatment that consumes resources. It is assumed that the release date of a job is a linear decreasing continuous function of the amount of a locally and globally constrained, continuously divisible resource (e.g., energy, catalyzer, financial outlay, gas). The problem is to find a sequence of jobs and a resource allocation that will minimize the maximum job completion time. Such a problem appears, for example, in the ingot preheating and hot-rolling process in steel mills. It is shown that the problem is strongly NP-hard. Some polynomially solvable cases of the problem and approximate algorithms with both experimental and worst-case analysis are presented. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 99–113, 1998     

Probabilistic analysis of an asymptotically optimal solution for the completion time variance problem

Scheduling a set of n jobs on a single machine so as to minimize the completion time variance is a well‐known NP‐hard problem. In this paper, we propose a sequence, which can be constructed in O(n log n) time, as a solution for the problem. Our primary concern is to establish the asymptotical optimality of the sequence within the framework of probabilistic analysis. Our main result is that, when the processing times are randomly and independently drawn from the same uniform distribution, the sequence is asymptotically optimal in the sense that its relative error converges to zero in probability as n increases. Other theoretical results are also derived, including: (i) When the processing times follow a symmetric structure, the problem has 2^{⌊(n−1)/2⌋} optimal sequences, which include our proposed sequence and other heuristic sequences suggested in the literature; and (ii) when these 2^{⌊(n−1)/2⌋} sequences are used as approximate solutions for a general problem, our proposed sequence yields the best approximation (in an average sense) while another sequence, which is commonly believed to be a good approximation in the literature, is interestingly the worst. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 373–398, 1999     

不可能差分分析时间复杂度通用计算公式的改进

研究Boura等和Derbez分别提出的不可能差分分析时间复杂度计算公式,根据实际攻击过程优化密钥排除的步骤,给出不可能差分分析实际攻击的时间复杂度计算的改进公式,进而利用两个分组密码算法模型将改进后公式计算的实际结果分别与Boura等的公式和Derbez的公式的计算结果进行对比,结果表明Boura等的公式计算结果既可能高于优化公式的实际分析计算的结果,也可能低于优化公式的实际分析计算的结果,而在轮子密钥独立时改进后公式的实际计算结果是Derbez公式的计算结果的2-1.2倍。     

机体/推进一体化飞行器动导数频域计算方法

运用Etkin非定常气动力模型,将谐波平衡法应用于复杂外形动导数辨识。计算结果表明:谐波平衡法和时域方法的动导数辨识结果一致,与实验值吻合,验证了程序的正确性和谐波平衡法的可靠性。采用谐波平衡法对类X-51高超声速机体/推进一体化飞行器WR-A进行动导数辨识,并与时域方法的计算结果比较,考察了该方法在复杂外形下数值模拟非定常流动和动导数辨识的能力。实验结果表明:对于WR-A这种复杂外形飞行器,谐波平衡法也能在保证精度的同时具有较高的计算效率。     

机载MIMO雷达稳健非均匀样本选择方法

针对杂波训练样本中混入干扰目标,导致空时自适应处理技术的杂波抑制性能下降问题,提出一种基于目标知识进行局部稀疏恢复的稳健训练样本挑选方法。该方法利用先验知识确定待检测单元中的目标区域,对整个角度-多普勒平面进行遍历,获得稀疏超完备基。通过变换矩阵对超完备基中对应的目标区域进行"挖空"处理,局部稀疏恢复出超分辨的杂波空时谱,获得杂波协方差矩阵估计。结合广义内积算法,实现非均匀训练样本挑选的过程。与常规结合广义内积方法相比,该方法对于不同干扰强度的训练样本,均有良好的检测效果。经仿真验证,所提方法的检验统计量之间区分度更加明显,对于干扰样本的挑选更加彻底,从而有效地提高了空时自适应处理技术的目标检测性能。     

Impacts of logistics information on sales: Evidence from Alibaba

Facing fierce competition from rivals, sellers in online marketplaces are eager to improve their sales by delivering items faster and more reliably. Because logistics quality can be known only after a transaction, sellers must identify effective ways to communicate logistics information to consumers. Drawing on the accessibility-diagnosticity framework, we theorize that the sales impacts of logistics information depend on its relative diagnostic value. Using data on 1493 items with 505,785 consumer reviews from an online marketplace, we examine how sales are affected by three information sources for logistics services: online word of mouth (WOM) about logistics, self-reported logistics services, and expected delivery time. We use an instrumental variable method to address the endogeneity issue between sales and WOM. We find that, ceteris paribus, consumers give more weight to WOM about logistics and delivery time when they make purchase decisions but less weight to self-reported logistics service. The effects of logistics information on sales are asymmetric for large and small sellers.     

具有坐标耦合和处理时滞的二阶离散多智能体系统的一致性

根据系统的拓扑结构、离散步长和旋转矩阵的旋转角,确定系统的渐近行为,给出多智能体系统达成二阶一致性的充要条件。证明了当0是拉普拉斯矩阵的一个简单特征值且离散步长、旋转角小于由代数方程确定的临界值时,会出现渐近一致性。数值模拟结果证明理论结果的正确性。设计了特征参数影响二阶一致性的相关案例,说明特征参数相关结论可为控制理论的一致收敛分析提供重要判据和理论支撑。     

Sojourn times in G/M/1 fork‐join networks

We consider a processing network in which jobs arrive at a fork‐node according to a renewal process. Each job requires the completion of m tasks, which are instantaneously assigned by the fork‐node to m task‐processing nodes that operate like G/M/1 queueing stations. The job is completed when all of its m tasks are finished. The sojourn time (or response time) of a job in this G/M/1 fork‐join network is the total time it takes to complete the m tasks. Our main result is a closed‐form approximation of the sojourn‐time distribution of a job that arrives in equilibrium. This is obtained by the use of bounds, properties of D/M/1 and M/M/1 fork‐join networks, and exploratory simulations. Statistical tests show that our approximation distributions are good fits for the sojourn‐time distributions obtained from simulations. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008