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     

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     

索赔离散到达的风险模型

讨论了索赔到达时间和索赔额均服从几何分布的风险模型 ,利用逐段决定马尔可夫骨架过程的广义生成算子去构造有关盈余过程的鞅 ,精确求解了模型的破产概率     

解决大功率柴油机曲轴箱通气装置漏油的途径

介绍了采用气体循环解决某型坦克发动机通气装置漏油问题的方法,通过建立进气系统模型、缸内过程模型、排气系统模型、气体循环系统模型,为进行精确的计算奠定了基础,同时也为硬件设计提供了方案.     

城市环境下单无人机测向定位航迹优化算法

为解决单架无人机在城市环境中对辐射源目标的定位问题,提出了一种基于环境预测法的单无人机测向定位航迹优化算法。使用交互多模型-扩展卡尔曼滤波进行视距和非视距信号混合环境下的目标估计。结合估计的目标位置和城市地理信息模型,基于视线追踪法求解信号遮挡区域和多径信号干扰区域。在滚动时域控制算法框架下生成无人机预测轨迹,以最大化Fisher信息矩阵行列式为测向定位评价准则,考虑建筑物障碍以及其对信号的遮挡和反射效应对无人机测向定位航迹的影响,控制无人机选择最优航向飞行。仿真结果表明,该方法能够使无人机在存在障碍、信号遮挡和多径干扰的环境下实现对目标的高精度测向定位,为解决城市环境下的单架无人机测向定位问题提供了新思路。     

TIN数字地形模型的通视性算法

数字地形模型的地形通视性分析有着广泛的应用,对TIN地形模型上两点间的通视性算法进行了研究、改进与实现.研究结果表明,视线与三角形相交法算法简单直观,但计算效率太低;改进的视线与边相交法数据结构简单,编程实现容易,适合地形数据结构单一的系统;而投影覆盖检测算法通用性好,适合地形数据结构多样的系统.     

Bolstering components for maximizing system lifetime

This article considers the problem of which component should be “bolstered” or “improved” in order to stochastically maximize the lifetime of a parallel system, series system, or in general, k-out-of-n system. Various ways of bolstering including active redundance, standby redundancy, and burn-in are studied. Also the method of reducing working temperature or stress level according to Arrhenius models is investigated. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 497–509, 1998     

利用验前信息的一种序贯检验方法——序贯验后加权检验方法

序贯验后加权检验方法是Bayes 统计观点在假设检验中的运用。本文提出了该方法的一般理论,给出了当总体的分布参数具有验前信息时的序贯检验方法。文中确定了决策区的划分,同时讨论了序贯截尾方案,给出了检验中可能犯两类错误的概率的上界,并将一般理论应用于产品的可靠性检验和再入飞行器随机落点的精度鉴定。由于运用了验前信息,因此能有效地在少量试验之下进行统计假设检验。本文所提供的方法对于昂贵产品试验结果的统计评定具有普遍意义。     

基于序列径向基函数的运载火箭蒙皮桁条结构轻质优化

以我国大型运载火箭薄壁加筋结构轻量化设计为研究背景,针对轴压下大直径大载荷蒙皮桁条结构开展后屈曲轻质优化研究。基于Python语言建立蒙皮桁条结构参数化模型,为确定结构的极限承载能力,开展蒙皮桁条结构后屈曲分析。针对蒙皮桁条结构轻质优化涉及离散的拓扑和连续的尺寸优化问题,提出基于近似模型和组合优化算法的序列近似优化方法,并利用近似最优解加速算法收敛,确定蒙皮桁条结构最优设计方案。工程算例结果表明,所提序列近似优化方法使大直径大载荷运载火箭蒙皮桁条结构减重效果明显,验证了方法的有效性。