多体存贮器有效频带分析

本文以排队论为工具建立了紧耦合多处理机系统存贮器的排队模型。通过对存贮体忙期的分析,得出了存贮器有效频带的解析表达式,研究了在保证存贮器有效频带最大的情况下,处理机的访存请求率λ、存贮体的服务率μ和存贮体数m 三者之间的关系。     

KDM 智能车的数学模型研究

本文确定了对载车数学模型构造方法,并试图以KDM-1移动机器人作为实例,用非完整系统力学当作分析工具,通过实验获得模型数据,并由实车行驶进行检验,几个重要参数由仿真试验校核。数学模型的仿真与室内的行车试验相对比的结果比较一致。对同类载车数学模型的建立提供了有效的方法。     

面向文本数据库管理系统的授权模型

构造新的授权模型以满足面向对象、语义、文本数据模型等对授权的需求是当前数据库技术的重要研究课题之一。本文提出了一个基于复杂对象数据模型的、以权主群及权体簇作为授权单位的多级授权模型,即MAM模型,并讨论了面向文本数据库授权系统的基本功能及基本操作。     

储油罐区灭火确定冷却兵力部署的模拟模型

本文提出了冷却燃烧罐和邻近罐时水枪应放置的位置的一系列数学描述原则,从而建立了油罐灭火冷却力量部署的模拟模型,该模型可方便地用于计算机模拟系统。     

一种性能驱动的时序规划方法

在超级计算机体系结构设计阶段 ,有必要进行时序规划 ,以尽早判断设计方案和性能指标的物理可实现性。提出一种性能驱动的时序规划方法 ,采用适于组件性能描述的时序性能模型 ,并按照线网权重分配路径延时余量 ,算法具有效率高、延时分配合理的优点     

火控雷达的仿真目标建模及实现

中外军队的实践证明 :模拟训练是一种最简便、成本低、效果好的训练方式。对于需要空情保障和训练成本高的雷达训练来说更是如此。探讨了火控雷达回波信号的模型建立及实施方案。     

A single‐period inventory placement problem for a serial supply chain

This article addresses the inventory placement problem in a serial supply chain facing a stochastic demand for a single planning period. All customer demand is served from stage 1, where the product is stored in its final form. If the demand exceeds the supply at stage 1, then stage 1 is resupplied from stocks held at the upstream stages 2 through N, where the product may be stored in finished form or as raw materials or subassemblies. All stocking decisions are made before the demand occurs. The demand is nonnegative and continuous with a known probability distribution, and the purchasing, holding, shipping, processing, and shortage costs are proportional. There are no fixed costs. All unsatisfied demand is lost. The objective is to select the stock quantities that should be placed different stages so as to maximize the expected profit. Under reasonable cost assumptions, this leads to a convex constrained optimization problem. We characterize the properties of the optimal solution and propose an effective algorithm for its computation. For the case of normal demands, the calculations can be done on a spreadsheet. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48:506–517, 2001     

Bayesian inference based on partial monitoring of components with applications to preventive system maintenance

Consider a binary, monotone system of n components. The assessment of the parameter vector, θ, of the joint distribution of the lifetimes of the components and hence of the reliability of the system is often difficult due to scarcity of data. It is therefore important to make use of all information in an efficient way. For instance, prior knowledge is often of importance and can indeed conveniently be incorporated by the Bayesian approach. It may also be important to continuously extract information from a system currently in operation. This may be useful both for decisions concerning the system in operation as well as for decisions improving the components or changing the design of similar new systems. As in Meilijson [12], life‐monitoring of some components and conditional life‐monitoring of some others is considered. In addition to data arising from this monitoring scheme, so‐called autopsy data are observed, if not censored. The probabilistic structure underlying this kind of data is described, and basic likelihood formulae are arrived at. A thorough discussion of an important aspect of this probabilistic structure, the inspection strategy, is given. Based on a version of this strategy a procedure for preventive system maintenance is developed and a detailed application to a network system presented. All the way a Bayesian approach to estimation of θ is applied. For the special case where components are conditionally independent given θ with exponentially distributed lifetimes it is shown that the weighted sum of products of generalized gamma distributions, as introduced in Gåsemyr and Natvig [7], is the conjugate prior for θ. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 551–577, 2001.     

An integer programming model for the weekly tour scheduling problem

We study a workforce planning and scheduling problem in which weekly tours of agents must be designed. Our motivation for this study comes from a call center application where agents serve customers in response to incoming phone calls. Similar to many other applications in the services industry, the demand for service in call centers varies significantly within a day and among days of the week. In our model, a weekly tour of an agent consists of five daily shifts and two days off, where daily shifts within a tour may be different from each other. The starting times of any two consecutive shifts, however, may not differ by more than a specified bound. Furthermore, a tour must also satisfy constraints regarding the days off, for example, it may be required that one of the days off is on a weekend day. The objective is to determine a collection of weekly tours that satisfy the demand for agents' services, while minimizing the total labor cost of the workforce. We describe an integer programming model where a weekly tour is obtained by combining seven daily shift scheduling models and days‐off constraints in a network flow framework. The model is flexible and can accommodate different daily models with varying levels of detail. It readily handles different days‐off rules and constraints regarding start time differentials in consecutive days. Computational results are also presented. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 607–624, 2001.     

舰炮系统的分布式交互仿真概述

论述了舰炮系统的分布式交互仿真 (DIS) ,建立了舰炮系统DIS模型并简述了各仿真模块的功能