Optimal capacity in a coordinated supply chain

We consider a supply chain in which a retailer faces a stochastic demand, incurs backorder and inventory holding costs and uses a periodic review system to place orders from a manufacturer. The manufacturer must fill the entire order. The manufacturer incurs costs of overtime and undertime if the order deviates from the planned production capacity. We determine the optimal capacity for the manufacturer in case there is no coordination with the retailer as well as in case there is full coordination with the retailer. When there is no coordination the optimal capacity for the manufacturer is found by solving a newsvendor problem. When there is coordination, we present a dynamic programming formulation and establish that the optimal ordering policy for the retailer is characterized by two parameters. The optimal coordinated capacity for the manufacturer can then be obtained by solving a nonlinear programming problem. We present an efficient exact algorithm and a heuristic algorithm for computing the manufacturer's capacity. We discuss the impact of coordination on the supply chain cost as well as on the manufacturer's capacity. We also identify the situations in which coordination is most beneficial. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Risk‐sensitive sizing of responsive facilities

We develop a risk‐sensitive strategic facility sizing model that makes use of readily obtainable data and addresses both capacity and responsiveness considerations. We focus on facilities whose original size cannot be adjusted over time and limits the total production equipment they can hold, which is added sequentially during a finite planning horizon. The model is parsimonious by design for compatibility with the nature of available data during early planning stages. We model demand via a univariate random variable with arbitrary forecast profiles for equipment expansion, and assume the supporting equipment additions are continuous and decided ex‐post. Under constant absolute risk aversion, operating profits are the closed‐form solution to a nontrivial linear program, thus characterizing the sizing decision via a single first‐order condition. This solution has several desired features, including the optimal facility size being eventually decreasing in forecast uncertainty and decreasing in risk aversion, as well as being generally robust to demand forecast uncertainty and cost errors. We provide structural results and show that ignoring risk considerations can lead to poor facility sizing decisions that deteriorate with increased forecast uncertainty. Existing models ignore risk considerations and assume the facility size can be adjusted over time, effectively shortening the planning horizon. Our main contribution is in addressing the problem that arises when that assumption is relaxed and, as a result, risk sensitivity and the challenges introduced by longer planning horizons and higher uncertainty must be considered. Finally, we derive accurate spreadsheet‐implementable approximations to the optimal solution, which make this model a practical capacity planning tool.© 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

非线性放大器对伪码测距误差的影响分析

在高精度伪码测距系统中,高功率放大器(HPA)是信号发射链路的重要组成部分,HPA会对发射信号引入非线性失真,进而恶化系统的伪码测距性能.通过理论推导和数值分析的方法,研究HPA的非线性特性对高精度伪码测距误差的影响,给出非线性放大条件下,伪码跟踪误差与放大器类型、放大器输出回退(OBO)、扩频码形参数等的定量关系.研究结果对工程上HPA的选择、功率余量的保留、基带扩频码形的设计等具有重要的参考价值.     

Strategic capacity decision‐making in a stochastic manufacturing environment using real‐time approximate dynamic programming

In this study, we illustrate a real‐time approximate dynamic programming (RTADP) method for solving multistage capacity decision problems in a stochastic manufacturing environment, by using an exemplary three‐stage manufacturing system with recycle. The system is a moderate size queuing network, which experiences stochastic variations in demand and product yield. The dynamic capacity decision problem is formulated as a Markov decision process (MDP). The proposed RTADP method starts with a set of heuristics and learns a superior quality solution by interacting with the stochastic system via simulation. The curse‐of‐dimensionality associated with DP methods is alleviated by the adoption of several notions including “evolving set of relevant states,” for which the value function table is built and updated, “adaptive action set” for keeping track of attractive action candidates, and “nonparametric k nearest neighbor averager” for value function approximation. The performance of the learned solution is evaluated against (1) an “ideal” solution derived using a mixed integer programming (MIP) formulation, which assumes full knowledge of future realized values of the stochastic variables (2) a myopic heuristic solution, and (3) a sample path based rolling horizon MIP solution. The policy learned through the RTADP method turned out to be superior to polices of 2 and 3. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010     

虚拟仪器水压仿真器液压站测试系统方案设计

水压仿真器是水下武器半实物仿真系统中模拟水下航行器航行深度变化的设备,其中液压泵站作为液压能源机构提供一定压力、流量的油液。为了对液压泵站系统运行进行动态监测,设计了一种基于虚拟仪器的水压仿真器液压泵站的测试系统方案,应用新型模型化仪器测量标准PXI总线系统,可充分利用计算机软硬件资源,完成液压系统压力和流量的智能化跟踪检测和信号分析,具有强大的人机交互和数据处理功能。     

A general strategic capacity planning model under demand uncertainty

Capacity planning decisions affect a significant portion of future revenue. In equipment intensive industries, these decisions usually need to be made in the presence of both highly volatile demand and long capacity installation lead times. For a multiple product case, we present a continuous‐time capacity planning model that addresses problems of realistic size and complexity found in current practice. Each product requires specific operations that can be performed by one or more tool groups. We consider a number of capacity allocation policies. We allow tool retirements in addition to purchases because the stochastic demand forecast for each product can be decreasing. We present a cluster‐based heuristic algorithm that can incorporate both variance reduction techniques from the simulation literature and the principles of a generalized maximum flow algorithm from the network optimization literature. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

海区变化对新型舰船海水淡化装置性能的影响

针对舰船远航时某新型海水淡化装置性能随海水盐度等因素变化而改变的问题,分析了该型海水淡化装置主要影响因素,并对其造水量进行了热力校核计算.实例计算结果表明,某航行海区较设计海区排污系数相对增大近25倍,造水量由原来的2 042 kg/h下降到1 847 kg/h,下降了9.55%.     

非平稳数据处理方法与瞬时频率

利用“经验模式分解”(EMD)方法,任何复杂的数集都能够被分解为有限且通常数量较少的“本征模式函数”。“本征模式函数”产生瞬时频率,最终结果表示为H ilbert谱规定的能量-频率-时间分布。应用“经验模式分解”方法表示自然现象中的传统非线性平衡系统及其数据的数值结果,同时给出实例展示了这种新方法的作用和效果。这种方法阐明了能量-频率-时间分布,进一步显示出对非线性非平稳系统的处理效果———精确化、形象化和可视化。     

超低频通信抗干扰性能分析

在分析和研究外军超低频通信系统基础上,针对超低频通信系统性能特点,结合现代无线通信干扰基本模式,分析了超低频通信系统优良的抗干扰性能。研究表明,超低频通信系统具有极强的抗干涉能力。     

基于光谱信息融合的发动机磨损状态监测

光谱分析技术操作简便、快捷, 是发动机磨损状态监测与故障诊断行之有效的主要手段。基于发动机磨损特征及其状态识别框架, 建立了其信息融合系统, 并结合实例, 分别应用磨损量信息融合、磨损率信息融合和磨损量与磨损率联合融合 3种方法, 得到发动机磨损工况的信任区间及其磨损状态。实践证明, 光谱信息融合方法可提高发动机磨损状态的识别率, 是发动机磨损状态监测的理想方法。