坦克分队遭遇战斗火力运用研究

根据遭遇战斗的特点,运用随机格斗、微分对策数理战术模型,研究坦克分队遭遇战斗最优火力运用策略问题.研究得出的结论符合坦克分队战术特点,为坦克分队指挥决策提供辅助作用.     

Appointment scheduling at a multidisciplinary outpatient clinic using stochastic programming

The purpose of this paper is to investigate the problem of constructing an appointment template for scheduling patients at a specific type of multidisciplinary outpatient clinic called an integrated practice unit (IPU). The focus is on developing and solving a stochastic optimization model for a back pain IPU in the face of random arrivals, an uncertain patient mix, and variable service times. The deterministic version of the problem is modeled as a mixed integer program with the objective of minimizing a weighted combination of clinic closing time (duration) and total patient waiting time (length of stay). A two‐stage stochastic program is then derived to account for the randomness and the sequential nature of the decisions. Although it was not possible to solve the two‐stage problem for even a limited number of scenarios, the wait‐and‐see (WS) problem was sufficiently tractable to provide a lower bound on the stochastic solution. The introduction of valid inequalities, limiting indices, and the use of special ordered sets helped to speed up the computations. A greedy heuristic was also developed to obtain solutions much more quickly. Out of practical considerations, it was necessary to develop appointment templates with time slots at fixed intervals, which are not available from the WS solution. The first to be derived was the expected value (EV) template that is used to find the expected value of the EV solution (EEV). This solution provides an upper bound on the objective function value of the two‐stage stochastic program. The average gap between the EEV and WS solutions was 18%. Results from extensive computational testing are presented for the EV template and for our adaptation of three other templates found in the literature. Depending on the relative importance of the two objective function metrics, the results demonstrate the trade‐off that exists between them. For the templates investigated, the “closing time” ranged from an average of 235 to 275 minutes for a 300‐minute session, while the corresponding “total patient time in clinic” ranged from 80 to 71 minutes.     

A decomposition algorithm applied to planning the interdiction of stochastic networks

We describe the application of a decomposition based solution method to a class of network interdiction problems. The problem of maximizing the probability of sufficient disruption of the flow of information or goods in a network whose characteristics are not certain is shown to be solved effectively by applying a scenario decomposition method developed by Riis and Schultz [Comput Optim Appl 24 (2003), 267–287]. Computational results demonstrate the effectiveness of the algorithm and design decisions that result in speed improvements. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

多媒体网络辅助英语教学模式中教师的作用

随着信息技术的迅猛发展,英语教学改革出现了新的契机。多媒体和网络以其形象化的表达方式,真实的语言环境,建构了开放的教学空间,优化了外语教学环境。这必然会引起外语教学从教材、教学方法、教学手段到整个教学过程的重大变革,大学英语教学模式也将随之发生深刻变化。如何适应这一变化,是教师应该重点考虑的问题。     

基于随机虚拟样机的某型自行火炮扭力轴动力仿真

依据随机动力学、多体系统动力学和数理统计理论,借助MSC\Adams仿真软件和MATLAB工具,提出随机虚拟样机的概念。并以某型自行火炮的扭力轴为例,在建立的虚拟样机上,实现不确定性因素下从底盘整体到悬挂系统、再到扭力轴的动力仿真。     

防空体系反制网电攻击的UML与Petri网模型

网电攻击装备的出现,给传统防空体系带来全面严峻的新威胁。通过分析"舒特"系统,得到网电攻击3种典型作战样式:物理摧毁、电子攻击和网络攻击,分别从物理层次、能量层次和网络层次探索了防空体系反制网电攻击策略。为描述防空体系反制网电攻击的对策、作战结构、作战步骤等问题,分别建立了统一建模语言(UML)和Petri网模型,从理论上初步探索了防空体系反制网电攻击的对策,具有一定的理论与现实意义。     

一类搜索型多对二随机格斗的获胜概率

研究搜索型多对二随机格斗战斗模型。假设格斗开始时A方有m件武器,B方有2件武器,B方处于隐蔽状态,格斗开始后B方可以直接对A方进行射击,A方需先搜索到B方后才能进行射击。双方各为同类武器,都是集火射击,所有开火都是独立的,每件武器开火射击直到毁伤对方才重新射击下一个目标。对搜索时间和毁伤间隔时间都服从一般分布的随机格斗模型,通过分析各状态的特征,利用状态概率分析方法和向后递归时间方法建立状态方程,求出了格斗处在各个状态的概率,并得到双方的获胜概率计算公式。     

Partial equilibrium in risk‐based production decisions

Characteristically, a small subset of operational problems admit risk neutrality when contingent claims methodology were used in their analysis. That is, for the majority of manufacturing and production problems, operating cash flows are not directly linked to prices of traded assets. However, to the extent that correlations can be estimated, the methodology's applicability to a broader set of operational problems is supported. Our article addresses this issue with the objective of extending the use of contingent claims techniques to a larger set of operational problems. In broad terms, this objective entails a partial equilibrium approach to the problem of valuing uncertain cash flows. To this end, we assume risk aversion and cast our approach within Merton's intertemporal capital asset pricing model. In this context, we formulate a “generic” production valuation model that is framed as an exercise in stochastic optimal control. The model is versatile in its characterization and can easily be adapted to accommodate a wide‐ranging set of risk‐based operational problems where the underlying sources of uncertainty are not traded. To obtain results, the model is recast as a stochastic dynamic program to be solved numerically. The article addresses a number of fundamental issues in the analysis risk based decision problems in operations. First, in the approach provided, decisions are analyzed under a properly defined risk structure. Second, the process of analysis leads to suitably adjusted probability distributions through which, appropriately discounted expectations are derived. Third, through consolidating existing concepts into a standard and adaptable framework, we extend the applicability of contingent claims methodology to a broader set of operational problems. The approach is advantageous as it obviates the need for exogenously specifying utility functions or discount rates.© 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Averaging frameworks for simulation optimization with applications to simulated annealing

We present two frameworks for designing random search methods for discrete simulation optimization. One of our frameworks is very broad (in that it includes many random search methods), whereas the other one considers a special class of random search methods called point‐based methods, that move iteratively between points within the feasible region. Our frameworks involve averaging, in that all decisions that require estimates of the objective function values at various feasible solutions are based on the averages of all observations collected at these solutions so far. Also, the methods are adaptive in that they can use information gathered in previous iterations to decide how simulation effort is expended in the current iteration. We show that the methods within our frameworks are almost surely globally convergent under mild conditions. Thus, the generality of our frameworks and associated convergence guarantees makes the frameworks useful to algorithm developers wishing to design efficient and rigorous procedures for simulation optimization. We also present two variants of the simulated annealing (SA) algorithm and provide their convergence analysis as example application of our point‐based framework. Finally, we provide numerical results that demonstrate the empirical effectiveness of averaging and adaptivity in the context of SA. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

基于影响网络与不完全信息多阶段博弈的作战行动序列模型及求解方法

拟制作战计划的关键是生成作战行动序列.考虑作战行动过程中的不确定性以及激烈对抗性,以影响网络分析作战行动和战场态势之间的相互影响,用不完全信息博弈分析敌对双方之间的对抗,建立了基于影响网络和不完全信息多阶段博弈的作战行动序列模型,并给出了求解方法.通过计算实例说明了模型及其求解方法.结果显示该模型生成的COA更适应于对抗环境.