校园网建设中的几个问题

通过介绍我院在建设校园网过程中的基本做法和初步经验,对网络技术特别是1000M以太网技术,进行了简单分析和研究,提出了基于Intel网络设备的千兆校园网解决方案,强调指出:建设先进高效的校园网,开展多媒体网络教学,创建信息化教学环境,是信息时代军事教育训练改革的必由之路。     

一类多维双重时序 AR(1)-MA(q) 模型的平稳性

讨论了一类多维双重时序ＡＲ（１）－ＭＡ（ｑ）模型的二阶平稳性问题。通过导出一组线性方程组，给出了这类模型二阶平稳的显式充分条件和必要条件，为验证模型的二阶平稳性提供了一个可行的途径。     

环形区域极点/协方差约束下的模型简化设计

提出离散随机系统模型简化的一种新方法,即环形区域极点／协方差约束下的模型简化方法。这种设计方法的基本思路是构造指定维数的降阶模型,使其匹配给定的环形区域极点和稳态协方差参数,在系统的动态特性和稳态特性方面逼近给定的满阶模型。文中导出了期望的简化模型的存在条件及解析表达式,并提供了一个数值算例。     

C~3I系统的决策时延分析

决策是C~3I 系统的核心问题之一。用Petri 网理论研究C~3I 系统的决策问题已取得了长足的进展。根据决策过程各阶段之所需时间具有随机性及不独立性的特点,以变迁发射时间不独立的随机Petri 网作为决策时延的建模与分析工具,并给出了这种随机Petri 网模型的一般分析方法。     

基于分布式排队网络的防空战术协同模型

分析了多个防空火力单元的作战过程,将战术BM/C3的控制协调决策抽象为决策策略。建立了多个火力单元协同作战的排队网络模型,并运用SPN理论对排队网络的运行机制进行了强有力的描述,有效地体现了防空作战过程中的威胁评估、目标分配等战术决策过程。这将为建立大型复杂排队网络,模拟仿真战役层面防空作战过程奠定基础。     

神经网络模型预测函数控制方法

在建立基于神经网络模型的非线性预测函数控制系统结构和基于BP网络非线性预测模型的基础上,提出了基于神经网络模型的非线性预测函数控制方法,并对其优化法等进行了讨论。通过与PID方法的仿真比较表明,预测函数控制方法具有抑制干扰能力强、跟踪性能好的特点,能够满足一些非线性系统的控制要求。     

GSPN的分析方法及其应用

随着计算机和信息技术的发展,广义随机Petri网(G SPN)作为一种图形化的建模工具,不仅可以对系统进行形式化的描述和快速原型开发,而且由于其具有坚实的数学理论基础,可以对系统进行正确性验证和性能评价,因此在系统的设计过程中,得到了广泛的应用。基于结构分析方法、可达图分析和数值分析方法讨论分析了G SPN,并给出了具体的算例,最后讨论了G SPN的应用领域。     

A model of supply-chain decisions for resource sharing with an application to ventilator allocation to combat COVID-19

We present a stochastic optimization model for allocating and sharing a critical resource in the case of a pandemic. The demand for different entities peaks at different times, and an initial inventory for a central agency are to be allocated. The entities (states) may share the critical resource with a different state under a risk-averse condition. The model is applied to study the allocation of ventilator inventory in the COVID-19 pandemic by FEMA to different U.S. states. Findings suggest that if less than 60% of the ventilator inventory is available for non-COVID-19 patients, FEMA's stockpile of 20 000 ventilators (as of March 23, 2020) would be nearly adequate to meet the projected needs in slightly above average demand scenarios. However, when more than 75% of the available ventilator inventory must be reserved for non-COVID-19 patients, various degrees of shortfall are expected. In a severe case, where the demand is concentrated in the top-most quartile of the forecast confidence interval and states are not willing to share their stockpile of ventilators, the total shortfall over the planning horizon (until May 31, 2020) is about 232 000 ventilator days, with a peak shortfall of 17 200 ventilators on April 19, 2020. Results are also reported for a worst-case where the demand is at the upper limit of the 95% confidence interval. An important finding of this study is that a central agency (FEMA) can act as a coordinator for sharing critical resources that are in short supply over time to add efficiency in the system. Moreover, through properly managing risk-aversion of different entities (states) additional efficiency can be gained. An additional implication is that ramping up production early in the planning cycle allows to reduce shortfall significantly. An optimal timing of this production ramp-up consideration can be based on a cost-benefit analysis.     

Pricing and inventory management during new product introduction when shortage creates hype

In this study, we analyze the joint pricing and inventory management during new product introduction when product shortage creates additional demand due to hype. We develop a two‐period model in which a firm launches its product at the beginning of the first period, before it observes sales in the two periods. The product is successful with an exogenous probability, or unsuccessful with the complementary probability. The hype in the second period is observed only when the product is successful. The firm learns the actual status of the product only after observing the first‐period demand. The firm must decide the stocking level and price of the product jointly at the beginning of each of the two periods. In this article, we derive some structural properties of the optimal prices and inventory levels, and show that (i) firms do not always exploit hype, (ii) firms do not always increase the price of a successful product in the second period, (iii) firms may price out an unsuccessful product in the first period if the success probability is above a threshold, and (iv) such a threshold probability is decreasing in the first‐period market potential of the successful product. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 304–320, 2015     

Chance‐constrained multi‐terminal network design problems

We consider a reliable network design problem under uncertain edge failures. Our goal is to select a minimum‐cost subset of edges in the network to connect multiple terminals together with high probability. This problem can be seen as a stochastic variant of the Steiner tree problem. We propose two scenario‐based Steiner cut formulations, study the strength of the proposed valid inequalities, and develop a branch‐and‐cut solution method. We also propose an LP‐based separation for the scenario‐based directed Steiner cut inequalities using Benders feasibility cuts, leveraging the success of the directed Steiner cuts for the deterministic Steiner tree problem. In our computational study, we test our branch‐and‐cut method on instances adapted from graphs in SteinLib Testdata Library with up to 100 nodes, 200 edges, and 17 terminals. The performance of our branch‐and‐cut method demonstrates the strength of the scenario‐based formulations and the benefit from adding the additional valid inequalities that we propose. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 321–334, 2015