Testing of software with an operational profile

One of the important features of any software system is its operational profile. This is simply the set of all operations that a software is designed to perform and the occurence probabilities of these operations. We present a new model on optimal software testing such that testing is done sequentially using a set of test cases. There may be failures due to the operations in each of these cases. The model parameters, consisting of testing costs and failure rates, all depend on the cases used and the operations performed. Our aim is to find the optimal testing durations in all of the cases in order to minimize the total expected cost. This problem leads to interesting decision models involving nonlinear programming formulations that possess explicit analytical solutions under reasonable assumptions. © 2000 John Wiley & Sons, Inc., Naval Research Logistics 47: 620–634, 2000     

无人机电磁弹射器的综合制动方法

利用直线电机实现无人机在短距离内可控地加速起飞已是固定翼无人机弹射起飞一种新的发展方向。为了使飞机分离后弹射台能在较短距离里完成制动,提出了直线电机弹射轨道末段定子实铁心涡流制动、运用Halbach永磁体阵列的涡流制动和橡胶阻尼制动等三种方式的综合方案,并分别对它们进行了分析计算。当弹射台的速度大于10m/s时,定子实铁心产生的涡流制动效果明显,当弹射台的速度低于3m/s时,定子实铁心涡流制动产生的制动力将迅速下降。Halbach永磁体阵列的涡流制动方式在飞机分离点开始实施,可以增加30%以上的制动效果。通过模型分析和碰撞试验,橡胶阻尼制动作为最后一级制动方式,能够有效吸收能量,实现在较短距离里的制动。     

Scheduling stochastic jobs with asymmetric earliness and tardiness penalties

We consider a stochastic counterpart of the well-known earliness-tardiness scheduling problem with a common due date, in which n stochastic jobs are to be processed on a single machine. The processing times of the jobs are independent and normally distributed random variables with known means and known variances that are proportional to the means. The due dates of the jobs are random variables following a common probability distribution. The objective is to minimize the expectation of a weighted combination of the earliness penalty, the tardiness penalty, and the flow-time penalty. One of our main results is that an optimal sequence for the problem must be V-shaped with respect to the mean processing times. Other characterizations of the optimal solution are also established. Two algorithms are proposed, which can generate optimal or near-optimal solutions in pseudopolynomial time. The proposed algorithms are also extended to problems where processing times do not satisfy the assumption in the model above, and are evaluated when processing times follow different probability distributions, including general normal (without the proportional relation between variances and means), uniform, Laplace, and exponential. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44, 531–557, 1997.     

改进分块局部最佳维纳滤波算法的干涉相位滤波

针对合成孔径雷达干涉相位滤波问题,提出了一种改进的分块局部最佳维纳滤波算法。该算法是加性高斯白噪声下的线性最小均方误差估计,利用目前图像滤波最前沿的技术——非局部技术,来联合估计图像的一、二阶矩。针对干涉相位中噪声的空变性,在应用中提出了两点改进:估计噪声的标准差时,用均值代替中值;根据噪声标准差的最大值和均值的比值,自适应地确定类的数量。仿真和实测数据表明,改进后的分块局部最佳维纳滤波算法是有效的,并优于其他三种算法。     

线性可调音速喷嘴工作特性仿真

为了满足组合发动机模态转换的要求,连续稳定调节推进剂流量十分关键。为此,针对气体推进剂,在常规音速喷嘴的基础上设计了一种可调音速喷嘴。通过塞锥改变音速喷嘴的节流面积,进而实现流量的连续调节。采用两次包络线方法设计塞锥型面,使得可调音速喷嘴具有线性的流量特性。采用计算流体动力学数值仿真研究可调音速喷嘴的工作特性。仿真结果表明反压小于临界反压时,可调音速喷嘴流量不受反压影响。可调音速喷嘴保持临界状态的临界反压比随流量的减小呈增大的趋势。线性可调音速喷嘴的流量与塞锥位置有较好的线性关系,其流量系数高且几乎不受塞锥位置的影响。     

对DES密码的一种新的线性分析

首先推广了变换的线性偏差的概念,然后利用它把密码体制线性偏差的数学描述也进行了推广,给出了DES密码的线性偏差与轮函数F的线性偏差的关系,确定了DES密码16轮以内各轮的线性偏差上界。     

一种基于神经网络的磁性目标定位方法

磁性目标定位问题可归结为一类非线性规划问题的求解 .该问题的最大特点就是其目标函数的计算过程极为繁琐 .而目标函数计算的快慢对磁定位的实时性有很大影响 .在详细研究了目标函数之后 ,给出了目标函数的一种神经网络结构实现 .由于该网络结构易于并行计算和VLSI实现 ,从而可使磁定位的实时性得到改善 .     

The impact of exponential smoothing forecasts on the bullwhip effect

An important phenomenon often observed in supply chain management, known as the bullwhip effect, implies that demand variability increases as one moves up the supply chain, i.e., as one moves away from customer demand. In this paper we quantify this effect for simple, two‐stage, supply chains consisting of a single retailer and a single manufacturer. We demonstrate that the use of an exponential smoothing forecast by the retailer can cause the bullwhip effect and contrast these results with the increase in variability due to the use of a moving average forecast. We consider two types of demand processes, a correlated demand process and a demand process with a linear trend. We then discuss several important managerial insights that can be drawn from this research. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 269–286, 2000     

Optimizing natural gas pipeline transmission with nonuniform elevation: A new initialization approach

In this paper, we develop an iterative piecewise linear approximation approach with a novel initialization method to solve natural gas pipeline transmission problems with the nonuniform network elevation. Previous approaches, such as energy minimization methods, cannot be applied to solve problems with the nonuniform network elevation because they exclude pressure range constraints, and thus provide solutions far from optimum. We propose a new initialization model that considers pressure range constraints and improves the optimality of the solutions and the computational efficiency. Furthermore, we extend the energy minimization methods and provide the necessary conditions under which the extended methods operate in networks with the nonuniform elevation. We test the performances of the methods with previously reported pipeline networks from the literature, with the open data set GasLib, and with our industrial collaborator. The initialization approach is shown to be more efficient than the method with fixed initial breakpoints. The newly proposed initialization approach generates solutions with a higher accuracy than the extended energy minimization methods, especially in large‐size networks. The proposed method has been applied to natural gas transmission planning by the China National Petroleum Corporation and has brought a direct profit increase of 330 million U.S. dollars in 2015‐2017.     

Shortest path interdiction problem with arc improvement recourse: A multiobjective approach

We consider the shortest path interdiction problem involving two agents, a leader and a follower, playing a Stackelberg game. The leader seeks to maximize the follower's minimum costs by interdicting certain arcs, thus increasing the travel time of those arcs. The follower may improve the network after the interdiction by lowering the costs of some arcs, subject to a cardinality budget restriction on arc improvements. The leader and the follower are both aware of all problem data, with the exception that the leader is unaware of the follower's improvement budget. The effectiveness of an interdiction action is given by the length of a shortest path after arc costs are adjusted by both the interdiction and improvement. We propose a multiobjective optimization model for this problem, with each objective corresponding to a different possible improvement budget value. We provide mathematical optimization techniques to generate a complete set of strategies that are Pareto‐optimal. Additionally, for the special case of series‐parallel graphs, we provide a dynamic‐programming algorithm for generating all Pareto‐optimal solutions.