Markets for surplus components with a strategic supplier

We study markets for surplus components, which allow manufacturers with excess component inventory to sell to firms with a shortage. Recent developments in internet commerce have the potential to greatly increase the efficiency of such markets. We develop a one‐period model in which a monopolist supplier sells to a number of independent manufacturers who are uncertain about demand for final goods. After uncertainty is resolved, the manufacturers have the opportunity to trade. Because uncertainty is over demand functions, the model allows us to endogenize both the price of final goods and the price of components in wholesale and surplus markets. We derive conditions on demand uncertainty that determine whether a surplus market will increase or decrease supplier profits. Increased costs of transacting on the surplus market may benefit manufacturers, because of the impact of these costs on the supplier's pricing power. The surplus market can decrease overall efficiency of the supply chain, since the benefit of better allocation of components may be outweighed by an increased double‐marginalization effect. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

基于SOA的防空指挥信息系统体系框架研究

针对各军兵种开发的指挥信息系统各自孤立,不能有效集成以满足未来网络中心战要求的问题,研究了基于SOA的系统集成技术及防空指挥信息系统的基本组成和结构,提出了一个可实现的基于SOA的防空指挥信息系统的分层结构模型,并应用SCA技术设计了一个防空指挥信息系统的原型系统。结果表明采用SCA可以实现防空指挥信息系统内子系统之间的基于SOA的无缝集成,提高了系统的可重用性、可扩展性。     

面向仿真的C4ISR系统领域分析与需求复用研究

面向C4ISR系统需求开发中的仿真支持问题,将复用作为一种的C4ISR系统需求模型的构建方法,可以快速形成一个有效的领域需求模型支持系统仿真验证。本文研究了C4ISR系统需求的领域性与领域需求共性问题,在此基础上研究了C4ISR系统需求工程中的需求框架、需求本体以及需求组件等不同粒度的复用方法,分别对上述三种方法在领域应用中的不同作用进行了对比分析。     

网络化指挥信息系统建设的软件构件技术

研究了基于构件技术建设网络化指挥信息系统的方法,以适应随需应变和快速开发这一新的作战要求。给出了框架、构件、扩展点等基本概念,提出了基于构件的指控系统框架、业务流程、系统重组方法,讨论了通用构件模型、共享信息模型、流程控制、构件获取和数据服务机制等系统建设的关键技术,探讨了指挥控制信息系统的建设途径,为发展未来指挥控制信息系统的建设提出了一种新思路。     

Reliability of a two-dimensional demand-based networked system with multistate components

Existing research on multistate system reliability has mainly focused on one-dimensional systems such as parallel systems, linear sliding window systems, and linearly consecutively connected systems. However, two-dimensional networked systems widely exist in real-world applications such as lighting systems, monitoring systems, and computer network systems. This research considers a two-dimensional networked system consisting of multistate components. The system fails if the cumulative performance of any row or any column cannot meet a predetermined demand. A novel reliability evaluation algorithm is proposed for the considered two-dimensional networked system by extending the universal generating function technique. Furthermore, the proposed model and reliability evaluation algorithm are extended to a two-dimensional networked system with phased missions. The proposed models and algorithms are illustrated by a matrix heating system in a thermoforming machine.     

A nonlinear continuous time optimal control model of dynamic pricing and inventory control with no backorders

In this paper, we present a continuous time optimal control model for studying a dynamic pricing and inventory control problem for a make‐to‐stock manufacturing system. We consider a multiproduct capacitated, dynamic setting. We introduce a demand‐based model where the demand is a linear function of the price, the inventory cost is linear, the production cost is an increasing strictly convex function of the production rate, and all coefficients are time‐dependent. A key part of the model is that no backorders are allowed. We introduce and study an algorithm that computes the optimal production and pricing policy as a function of the time on a finite time horizon, and discuss some insights. Our results illustrate the role of capacity and the effects of the dynamic nature of demand in the model. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

On the (S − 1, S) lost sales inventory model with priority demand classes

In this paper an inventory model with several demand classes, prioritised according to importance, is analysed. We consider a lot‐for‐lot or (S ? 1, S) inventory model with lost sales. For each demand class there is a critical stock level at and below which demand from that class is not satisfied from stock on hand. In this way stock is retained to meet demand from higher priority demand classes. A set of such critical levels determines the stocking policy. For Poisson demand and a generally distributed lead time, we derive expressions for the service levels for each demand class and the average total cost per unit time. Efficient solution methods for obtaining optimal policies, with and without service level constraints, are presented. Numerical experiments in which the solution methods are tested demonstrate that significant cost reductions can be achieved by distinguishing between demand classes. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 593–610, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10032     

一种具有优先级的MAC协议性能分析

在移动通信中,为了满足高动态终端对接入的高要求,设计了一种带有优先级的随机预约/按需分配相结合的MAC协议RRDAMA-P(random reserve/demand assignment multiple access protocol with priority),并利用Opnet软件进行了建模仿真,仿真结果表明,RRDAMA-P协议不仅可以满足终端的优先级要求,而且实现了更好的吞吐量和时延性能。     

一种基于多目标优化的QoS路由交互式算法

为了满足通信网络中一些特定业务对于多个网络指标性能的同时要求 ,研究了一类基于多目标决策的QoS路由算法。通过选取带宽作为约束条件 ,把时延和丢失率作为优化目标 ,建立了QoS路由选择的多目标非线性整数规划模型 ,并给出了一种求解模型的交互式算法。该算法通过逐步调整目标函数的上界 ,压缩目标函数的搜索空间来满足决策者的要求和网络条件。实例计算结果表明了算法的可行性     

Energy‐efficient scheduling for sustainable manufacturing systems with renewable energy resources

Environmentally friendly energy resources open a new opportunity to tackle the problem of energy security and climate change arising from wide use of fossil fuels. This paper focuses on optimizing the allocation of the energy generated by the renewable energy system to minimize the total electricity cost for sustainable manufacturing systems under time‐of‐use tariff by clipping the peak demand. A rolling horizon approach is adopted to handle the uncertainty caused by the weather change. A nonlinear mathematical programming model is established for each decision epoch based on the predicted energy generation and the probability distribution of power demand in the manufacturing plant. The objective function of the model is shown to be convex, Lipchitz‐continuous, and subdifferentiable. A generalized benders decomposition method based on the primal‐dual subgradient descent algorithm is proposed to solve the model. A series of numerical experiments is conducted to show the effectiveness of the solution approach and the significant benefits of using the renewable energy resources.     

Optimal FCFS allocation rules for periodic‐review assemble‐to‐order systems

In Assemble‐To‐Order (ATO) systems, situations may arise in which customer demand must be backlogged due to a shortage of some components, leaving available stock of other components unused. Such unused component stock is called remnant stock. Remnant stock is a consequence of both component ordering decisions and decisions regarding allocation of components to end‐product demand. In this article, we examine periodic‐review ATO systems under linear holding and backlogging costs with a component installation stock policy and a First‐Come‐First‐Served (FCFS) allocation policy. We show that the FCFS allocation policy decouples the problem of optimal component allocation over time into deterministic period‐by‐period optimal component allocation problems. We denote the optimal allocation of components to end‐product demand as multimatching. We solve the multi‐matching problem by an iterative algorithm. In addition, an approximation scheme for the joint replenishment and allocation optimization problem with both upper and lower bounds is proposed. Numerical experiments for base‐stock component replenishment policies show that under optimal base‐stock policies and optimal allocation, remnant stock holding costs must be taken into account. Finally, joint optimization incorporating optimal FCFS component allocation is valuable because it provides a benchmark against which heuristic methods can be compared. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 158–169, 2015     

考虑战损件回收再造的战场军需备件供应优化研究

在考虑军需备件需求和战损件修复不确定性的条件下,研究了战场上军需备件供应优化问题,建立了优化问题的数学模型,证明了模型的凸函数特性,给出了模型的最优解析解计算方法.     

A dynamic,nonstationary inventory problem for a price/quantity setting firm

A dynamic and nonstationary model is formulated for a firm which attempts to minimize total expected costs over a finite planning horizon. The control variables are price and production. The price p and the demand ζ are linked through the relationship ζ = g(p) + η, where g(p) is the riskless demand curve and η is a random variable. The general model allows for proportional ordering costs, convex holding and stockout costs, downward sloping riskless demand curve, backlogging, partial backlogging, lost sales, partial spoilage of inventory, and two modes of collecting revenue. Sufficient conditions are developed for this problem to have an optimal policy which resembles the single critical number policy known from stochastic inventory theory. It is also shown what set of parameters will satisfy these sufficiency conditions.     

Dynamic learning,pricing, and ordering by a censored newsvendor

We address the problem of determining optimal ordering and pricing policies in a finite‐horizon newsvendor model with unobservable lost sales. The demand distribution is price‐dependent and involves unknown parameters. We consider both the cases of perishable and nonperishable inventory. A very general class of demand functions is studied in this paper. We derive the optimal ordering and pricing policies as unique functions of the stocking factor (which is a linear transformation of the safety factor). An important expression is obtained for the marginal expected value of information. As a consequence, we show when lost sales are unobservable, with perishable inventory the optimal stocking factor is always at least as large as the one given by the single‐period model; however, if inventory is nonperishable, this result holds only under a strong condition. This expression also helps to explain why the optimal stocking factor of a period may not increase with the length of the problem. We compare this behavior with that of a full information model. We further examine the implications of the results to the special cases when demand uncertainty is described by additive and multiplicative models. For the additive case, we show that if demand is censored, the optimal policy is to order more as well as charge higher retail prices when compared to the policies in the single‐period model and the full information model. We also compare the optimal and myopic policies for the additive and multiplicative models. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Resource allocation with lumpy demand: To speed or not to speed?

In the classical EPQ model with continuous and constant demand, holding and setup costs are minimized when the production rate is no larger than the demand rate. However, the situation may change when demand is lumpy. We consider a firm that produces multiple products, each having a unique lumpy demand pattern. The decision involves determining both the lot size for each product and the allocation of resources for production rate improvements among the products. We find that each product's optimal production policy will take on only one of two forms: either continuous production or lot‐for‐lot production. The problem is then formulated as a nonlinear nonsmooth knapsack problem among products determined to be candidates for resource allocation. A heuristic procedure is developed to determine allocation amounts. The procedure decomposes the problem into a mixed integer program and a nonlinear convex resource allocation problem. Numerical tests suggest that the heuristic performs very well on average compared to the optimal solution. Both the model and the heuristic procedure can be extended to allow the company to simultaneously alter both the production rates and the incoming demand lot sizes through quantity discounts. Extensions can also be made to address the case where a single investment increases the production rate of multiple products. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

空防对抗武器装备对比优势评估模型

针对战役对抗准备和兵力部署的需要,根据兰切斯特动态方程,从作战能力入手,建立了空防对抗武器装备对比优势评估模型,提出了一种异类武器装备对比优势的定量计算方法。给出了应用该方法的具体步骤,通过算例分析,验证了模型的合理性,该模型对其他武器装备的对比优势评估具有一定的参考价值。     

基于作战任务的多机种故障备件需求模型

通过分析战时故障备件的需求特点,对备件的工作时间进行讨论,改进了传统的单机故障备件需求模型。根据多机种协同作战任务的不同,引入备件工作运行比的概念,在考虑飞机是否战损的前提下,建立了基于作战任务的多机种故障备件需求模型。算例分析证明了模型的有效性。     

Capacity expansion under a service‐level constraint for uncertain demand with lead times

For a service provider facing stochastic demand growth, expansion lead times and economies of scale complicate the expansion timing and sizing decisions. We formulate a model to minimize the infinite horizon expected discounted expansion cost under a service‐level constraint. The service level is defined as the proportion of demand over an expansion cycle that is satisfied by available capacity. For demand that follows a geometric Brownian motion process, we impose a stationary policy under which expansions are triggered by a fixed ratio of demand to the capacity position, i.e., the capacity that will be available when any current expansion project is completed, and each expansion increases capacity by the same proportion. The risk of capacity shortage during a cycle is estimated analytically using the value of an up‐and‐out partial barrier call option. A cutting plane procedure identifies the optimal values of the two expansion policy parameters simultaneously. Numerical instances illustrate that if demand grows slowly with low volatility and the expansion lead times are short, then it is optimal to delay the start of expansion beyond when demand exceeds the capacity position. Delays in initiating expansions are coupled with larger expansion sizes. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

The continuous‐time single‐sourcing problem with capacity expansion opportunities

This paper develops a new model for allocating demand from retailers (or customers) to a set of production/storage facilities. A producer manufactures a product in multiple production facilities, and faces demand from a set of retailers. The objective is to decide which of the production facilities should satisfy each retailer's demand, in order minimize total production, inventory holding, and assignment costs (where the latter may include, for instance, variable production costs and transportation costs). Demand occurs continuously in time at a deterministic rate at each retailer, while each production facility faces fixed‐charge production costs and linear holding costs. We first consider an uncapacitated model, which we generalize to allow for production or storage capacities. We then explore situations with capacity expansion opportunities. Our solution approach employs a column generation procedure, as well as greedy and local improvement heuristic approaches. A broad class of randomly generated test problems demonstrates that these heuristics find high quality solutions for this large‐scale cross‐facility planning problem using a modest amount of computation time. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.