Dynamic coordination of production planning and sales admission control in the presence of a spot market

We consider the decision‐making problem of dynamically scheduling the production of a single make‐to stock (MTS) product in connection with the product's concurrent sales in a spot market and a long‐term supply channel. The spot market is run by a business to business (B2B) online exchange, whereas the long‐term channel is established by a structured contract. The product's price in the spot market is exogenous, evolves as a continuous time Markov chain, and affects demand, which arrives sequentially as a Markov‐modulated Poisson process (MMPP). The manufacturer is obliged to fulfill demand in the long‐term channel, but is able to rein in sales in the spot market. This is a significant strategic decision for a manufacturer in entering a favorable contract. The profitability of the contract must be evaluated by optimal performance. The current problem, therefore, arises as a prerequisite to exploring contracting strategies. We reveal that the optimal strategy of coordinating production and sales is structured by the spot price dependent on the base stock and sell‐down thresholds. Moreover, we can exploit the structural properties of the optimal strategy to conceive an efficient algorithm. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

基于排队论模型的轮询协议数据链系统时延分析

基于数据链系统的作战方式已经成为了现代化战场的主流,战争中战机稍纵即逝,因此,分析数据链系统的信息传输时延特性意义重大。针对数据链系统信息传输时延问题,分析了数据链系统传输命令消息,目标消息以及中继消息的一般过程,并给出了排队论模型。根据排队论的相关知识得到了轮询协议数据链传输时延的公式,最后利用仿真软件进行了分析研究。     

基于排队论的油料供给最优化分析

通过有限源排队系统的理论,分析油料供给工作中在满足一定的可靠性要求下的最优设计与最优分配问题,同时结合计算机技术,提出了求数值解的方法。     

利用排队模型优化保障设备数量

就如何将排队论法应用于确定保障设备数量的方法进行了分析和研究,得出一种可行的确定保障设备数量的方法,对研制过程中科学地规划保障设备的数量提供了借鉴,对提高装备的保障力和战斗力以及降低全寿命周期费用具有重要意义.     

混合排队规则的战术装备维修保障系统分析

首先将战术装备维修保障过程描述为M/M/c/k混合规则的排队过程,其损坏装备到达服从相互独立的泊松分布,维修时间服从相互独立的指数分布。同时考虑系统的到达率和维修率随系统中装备数量的变化,重要战损装备等待维修时的不耐烦性以及重要装备对一般装备的强占性优先权情况,结合战术装备维修保障系统的结构和规模,建立战术装备维修保障M/M/3/12排队模型。列出模型的平衡方程,采用矩阵的分析方法得到重要装备和一般装备的稳态分布表达式,并以队长为指标进行了系统性能的计算。     

Waiting time analysis of the M/G/1 queue with finite retrial group

We consider an M/G/1 retrial queue with finite capacity of the retrial group. First, we obtain equations governing the dynamic of the waiting time. Then, we focus on the numerical inversion of the density function and the computation of moments. These results are used to approximate the waiting time of the M/G/1 queue with infinite retrial group for which direct analysis seems intractable. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

基于Stateflow的排队系统仿真方法

论述了排队系统与Stateflow相关概念，利用有限状态机理论与面向对象编程思想，提出了建立基于Stateflow排队系统模型的分析步骤，阐述了应用Stateflow对排队系统进行建模与仿真的方法，使用Stateflow对M／M／1／∞／∞／FIFO类型排队系统进行了具体的建模与仿真。仿真结果表明，基于Stateflow的模型与仿真能够有效地描述排队系统的统计特性，并具有可视化、流程化和层次化的特点。     

一个具有相互独立、不同分布服务时间序列的排队模型

讨论的排队模型 ,放宽了GI/G/1系统中“服务时间独立同分布”的限制 ,只要求各服务时间相互独立 ,因而较GI/G/1排队模型能更合理地拟合实际问题 .在此较宽的条件下 ,利用补充变量的方法 ,求得了该排队系统队长的瞬时分布     

分布式数据库系统中数据一致性维护方法研究

分布式数据库系统是数据库领域中的一个主要研究方向 ,数据一致性维护是分布式数据库系统中的一个非常关键的技术问题。在深入分析和比较各种维护数据一致性方法的基础上 ,提出了一种较为有效的维护数据一致性的方法 ,详细论述了该方法如何解决并发执行引起的冲突问题 ,以及如何利用消息队列机制保持各数据副本的一致     

Stein–Chen approximation and error bounds for order fill rates in assemble‐to‐order systems

Assemble‐to‐order (ATO) is an important operational strategy for manufacturing firms to achieve quick response to customer orders while keeping low finished good inventories. This strategy has been successfully used not only by manufacturers (e.g., Dell, IBM) but also by retailers (e.g., Amazon.com). The evaluation of order‐based performance is known to be an important but difficult task, and the existing literature has been mainly focused on stochastic comparison to obtain performance bounds. In this article, we develop an extremely simple Stein–Chen approximation as well as its error‐bound for order‐based fill rate for a multiproduct multicomponent ATO system with random leadtimes to replenish components. This approximation gives an expression for order‐based fill rate in terms of component‐based fill rates. The approximation has the property that the higher the component replenishment leadtime variability, the smaller the error bound. The result allows an operations manager to analyze the improvement in order‐based fill rates when the base‐stock level for any component changes. Numerical studies demonstrate that the approximation performs well, especially when the demand processes of different components are highly correlated; when the components have high base‐stock levels; or when the component replenishment leadtimes have high variability. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012