Approximation methods for the analysis of a multicomponent,multiproduct assemble‐to‐order system

In this article, we consider the performance evaluation of a multicomponent, multiproduct assemble‐to‐order (ATO) system. Each component is managed independently using a base‐stock policy at a supply facility with limited production capacity and an infinite buffer. The arrivals of demands follow a multivariate Poisson process and unfilled demands are backlogged. Because exact analysis of the proposed system is not feasible, we propose two approximation methods which provide upper and lower bounds for various performance measures such as fill rate, average waiting time, and average number of backorders of the proposed system. Our computational experiments demonstrate the effectiveness of the two approximation methods under various system settings. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Inventory management with advance capacity information

An important aspect of supply chain management is dealing with demand and supply uncertainty. The uncertainty of future supply can be reduced if a company is able to obtain advance capacity information (ACI) about future supply/production capacity availability from its supplier. We address a periodic‐review inventory system under stochastic demand and stochastic limited supply, for which ACI is available. We show that the optimal ordering policy is a state‐dependent base‐stock policy characterized by a base‐stock level that is a function of ACI. We establish a link with inventory models that use advance demand information (ADI) by developing a capacitated inventory system with ADI, and we show that equivalence can only be set under a very specific and restrictive assumption, implying that ADI insights will not necessarily hold in the ACI environment. Our numerical results reveal several managerial insights. In particular, we show that ACI is most beneficial when there is sufficient flexibility to react to anticipated demand and supply capacity mismatches. Further, most of the benefits can be achieved with only limited future visibility. We also show that the system parameters affecting the value of ACI interact in a complex way and therefore need to be considered in an integrated manner. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Multi‐period maintenance scheduling of tree networks with minimum flow disruption

We introduce a multi‐period tree network maintenance scheduling model and investigate the effect of maintenance capacity restrictions on traffic/information flow interruptions. Network maintenance refers to activities that are performed to keep a network operational. For linear networks with uniform flow between every pair of nodes, we devise a polynomial‐time combinatorial algorithm that minimizes flow disruption. The spiral structure of the optimal maintenance schedule sheds insights into general network maintenance scheduling. The maintenance problem on linear networks with a general flow structure is strongly NP‐hard. We formulate this problem as a linear integer program, derive strong valid inequalities, and conduct a polyhedral study of the formulation. Polyhedral analysis shows that the relaxation of our linear network formulation is tight when capacities and flows are uniform. The linear network formulation is then extended to an integer program for solving the tree network maintenance scheduling problem. Preliminary computations indicate that the strengthened formulations can solve reasonably sized problems on tree networks and that the intuitions gained from the uniform flow case continue to hold in general settings. Finally, we extend the approach to directed networks and to maintenance of network nodes. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Cyclic scheduling in robotic flowshops with bounded work‐in‐process levels

This study addresses cyclic scheduling in robotic flowshops with bounded work‐in‐process (WIP) levels. The objective is to minimize the cycle time or, equivalently, to maximize the throughput, under the condition that the WIP level is bounded from above by a given integer number. We present several strongly polynomial algorithms for the 2‐cyclic robotic flowshop scheduling problems for various WIP levels. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 58: 1–16, 2011     

基于随机时间影响网络的联合火力打击方案评估

联合火力打击方案评估是作战筹划和指挥决策的核心问题之一,对于打击手段的选择、战法的运用等具有重要的影响,其难点是在不确定条件下有效地建立作战方案到使命目标达成效果之间的映射关系.作战仿真方法往往存在突出的低效率问题,而解析模型的方法难以充分反映目标体系的内部联系和整体效果.目前概率推理模型广泛应用于军事领域的作战方案评...     

随机共振用于非周期信号处理的仿真

介绍了双稳系统及其数学模型,给出了该系统应用于非周期信号处理的应用模型,进行了仿真实验并给出了实验结果。在此基础上,对非周期随机共振信号处理的物理机制进行了分析。结果表明,非周期随机共振信号处理与传统的周期随机共振信号处理的机制类似,也是信号、噪声和双稳系统共同作用的结果。     

基于Langevin型随机共振的水中目标线谱检测

将Langevin型双稳态随机共振系统应用于水声时变线谱信号的检测,提出了设计水声线谱检测系统可以利用的外在参数。在水听器端建立了时变线谱模型,考查了随机共振系统对水声环境的适应能力。实验发现在信噪比变化、声压起伏、线谱漂移等情况下,系统都能较好的工作,为水声领域新型线谱检测系统的设计提供了依据。     

基于多预测器的高光谱图像无损压缩

数据压缩是高光谱图像处理应用中的一个关键问题。在分析高光谱数据相关性特点的基础上,提出了一种方向可选的多预测器数据压缩框架。将新的框架应用于单波段和多波段的预测压缩方案,分别得到复杂性不同的两种无损压缩流程。计算机仿真结果表明了该框架的有效性。     

Dynamic order acceptance and capacity planning on a single bottleneck resource

We present a tactical decision model for order acceptance and capacity planning that maximizes the expected profits from accepted orders, allowing for aggregate regular as well as nonregular capacity. The stream of incoming order arrivals is the main source of uncertainty in dynamic order acceptance and the company only has forecasts of the main properties of the future incoming projects. Project proposals arrive sequentially with deterministic interarrival times and a decision on order acceptance and capacity planning needs to be made each time a proposal arrives and its project characteristics are revealed. We apply stochastic dynamic programming to determine a profit threshold for the accept/reject decision as well as to deterministically allocate a single bottleneck resource to the accepted projects, both with an eye on maximizing the expected revenues within the problem horizon. We derive a number of managerial insights based on an analysis of the influence of project and environmental characteristics on optimal project selection and aggregate capacity usage. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

The impact of component commonality on composite assembly policies

Assemble in Advance (AIA) policy reduces assembly cost due to advance planning, while Assemble to Order (ATO) policy eliminates assembly of excessive (more than demanded) units. The tradeoffs between the two policies have been studied in the past for single product environments. Moreover, it was shown that it is beneficial to employ AIA and ATO simultaneously. In this article, we study the employment of such a composite assembly policy in a multiproduct environment with component commonality. When common components are used, ATO may also enable us to benefit from the risk pooling effect. We provide important managerial insights such as: the multiperiod problem is myopic and changes in inventory levels due to the use of common components, and demonstrate the potential profit increase compared to other policies.© 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007