谱分析方法在仿真结果分析中的运用

文中给出了谱估计的分析，并将它直接应用于仿真系统输出量的特性分析。对于仿真的可信性问题，讨论了相容性检验方法，特别是小子样现场试验下，仿真与现场试验之间的一致性问题。     

复合材料圆锥壳稳定性分析的传递函数法

基于线弹性小变形理论， 利用Ｆｏｕｒｉｅｒ级数展开、Ｌａｐｌａｃｅ 变换和摄动方法， 建立了复合材料薄壁圆锥壳的静力响应、频率响应、自由振动与屈曲特征值问题的渐近传递函数解。构造了复杂边界条件、中间带支撑、变锥度及阶梯变厚度圆锥壳的传递函数解。数值计算结果表明该方法具有很高的计算精度。     

目标宽频带RCS的快速算法研究

目标宽带RCS预估算法一直是计算电磁学的一个研究热点,本文分别研究了渐近波形估计技术（AWE）与最佳一致逼近技术在宽频带RCS预估领域内的应用。首先,介绍了传统矩量法计算RCS的原理,并分析了两种快速算法的计算过程。然后,采用这两种技术,分别计算了简易飞机模型的RCS值,并对这两种方法进行比较。计算结果表明相比传统的矩量法,这两种方法在不影响精度的前提下大大提高了计算效率。同时,相比渐近波形估计技术,最佳一致逼近技术在节省内存,节约时间方面更具优势。最后,采用最佳一致逼近理论,结合电磁计算软件,实现较大尺寸目标的宽频带RCS的计算。     

软件分域测试可靠性评估的注记

软件可靠性评估是软件可靠性研究的重要问题.文中通过反例证明了分域测试的Thayer Lipow Nel son评估方法是不正确的,将样本点排序法用于分域产生可靠性评估,获得了软件可靠性置信下限.最后给出一个实例说明该方法的可行性.     

Value management of diagnostic equipment with cancelation,no‐show,and emergency patients

Magnetic resonance imaging and other multifunctional diagnostic facilities, which are considered as scarce resources of hospitals, typically provide services to patients with different medical needs. This article examines the admission policies during the appointment management of such facilities. We consider two categories of patients: regular patients who are scheduled in advance through an appointment system and emergency patients with randomly generated demands during the workday that must be served as soon as possible. According to the actual medical needs of patients, regular patients are segmented into multiple classes with different cancelation rates, no‐show probabilities, unit value contributions, and average service times. Management makes admission decisions on whether or not to accept a service request from a regular patient during the booking horizon to improve the overall value that could be generated during the workday. The decisions should be made by considering the cancelation and no‐show behavior of booked patients as well as the emergency patients that would have to be served because any overtime service would lead to higher costs. We studied the optimal admission decision using a continuous‐time discrete‐state dynamic programming model. Identifying an optimal policy for this discrete model is analytically intractable and numerically inefficient because the state is multidimensional and infinite. We propose to study a deterministic counterpart of the problem (i.e., the fluid control problem) and to develop a time‐based fluid policy that is shown to be asymptotically optimal for large‐scale problems. Furthermore, we propose to adopt a mixed fluid policy that is developed based on the information obtained from the fluid control problem. Numerical experiments demonstrate that this improved policy works effectively for small‐scale problems. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 287–304, 2016     

仿真信号模糊一致性分析与风险评估方法

为了完善基于置信区间的仿真信号一致性分析方法,考虑了置信区间与接收区间的长度匹配问题,定义来最佳样本容量,并在此基础上提出了基于D-S证据理论的仿真信号模糊一致性分析方法。同时为了对信号仿真模型的风险进行定量评估,建立了信号仿真模型风险系数函数,得到多参数仿真信号风险系数向量,以此给决策者和/或仿真用户提供决策支持。最后,用水中兵器仿真试验中水中目标辐射噪声仿真的应用实例加以说明。     

Estimating the point availability with right‐censored data

The point availability of a one‐unit system at a specified time is defined as the probability that the component is operating at that time. When both operating time and repair time are subject to random (right) censorship, we propose an asymptotic nonparametric approach for constructing confidence intervals for the point availability of the system. The technique is based on the fact that a product limit estimator converges to a Gaussian process. The method is also extended to finding confidence intervals for the point availability of a complex system using the δ‐Method. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 119–127, 1999     

Scheduling a production–distribution system to optimize the tradeoff between delivery tardiness and distribution cost

We consider a make‐to‐order production–distribution system with one supplier and one or more customers. A set of orders with due dates needs to be processed by the supplier and delivered to the customers upon completion. The supplier can process one order at a time without preemption. Each customer is at a distinct location and only orders from the same customer can be batched together for delivery. Each delivery shipment has a capacity limit and incurs a distribution cost. The problem is to find a joint schedule of order processing at the supplier and order delivery from the supplier to the customers that optimizes an objective function involving the maximum delivery tardiness and the total distribution cost. We first study the solvability of various cases of the problem by either providing an efficient algorithm or proving the intractability of the problem. We then develop a fast heuristic for the general problem. We show that the heuristic is asymptotically optimal as the number of orders goes to infinity. We also evaluate the performance of the heuristic computationally by using lower bounds obtained by a column generation approach. Our results indicate that the heuristic is capable of generating near optimal solutions quickly. Finally, we study the value of production–distribution integration by comparing our integrated approach with two sequential approaches where scheduling decisions for order processing are made first, followed by order delivery decisions, with no or only partial integration of the two decisions. We show that in many cases, the integrated approach performs significantly better than the sequential approaches. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

Replicated batch means for steady‐state simulations

This paper studies a new steady‐state simulation output analysis method called replicated batch means in which a small number of replications are conducted and the observations in these replications are grouped into batches. This paper also introduces and compares methods for selecting the initial state of each replication. More specifically, we show that confidence intervals constructed by the replicated batch means method are valid for large batch sizes and derive expressions for the expected values and variances of the steady‐state mean and variance estimators for stationary processes and large sample sizes. We then use these expressions, analytical examples, and numerical experiments to compare the replicated batch means method with the standard batch means and multiple replications methods. The numerical results, which are obtained from an AR(1) process and a small, nearly‐decomposable Markov chain, show that the multiple replications method often gives confidence intervals with poorer coverage than the standard and replicated batch means methods and that the replicated batch means method, implemented with good choices of initialization method and number of replications, provides confidence interval coverages that range from being comparable with to being noticeably better than coverages obtained by the standard batch means method. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006