On parallel machine replacement problems with general replacement cost functions and stochastic deterioration

The parallel machine replacement problem consists of finding a minimum cost replacement policy for a finite population of economically interdependent machines. In this paper, we formulate a stochastic version of the problem and analyze the structure of optimal policies under general classes of replacement cost functions. We prove that for problems with arbitrary cost functions, there can be optimal policies where a machine is replaced only if all machines in worse states are replaced (Worse Cluster Replacement Rule). We then show that, for problems with replacement cost functions exhibiting nonincreasing marginal costs, there are optimal policies such that, in any stage, machines in the same state are either all kept or all replaced (No‐Splitting Rule). We also present an example that shows that economies of scale in replacement costs do not guarantee optimal policies that satisfy the No‐Splitting Rule. These results lead to the fundamental insight that replacement decisions are driven by marginal costs, and not by economies of scale as suggested in the literature. Finally, we describe how the optimal policy structure, i.e., the No‐Splitting and Worse Cluster Replacement Rules, can be used to reduce the computational effort required to obtain optimal replacement policies. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

Bayesian analysis of queues with impatient customers: Applications to call centers

Queuing models have been extensively used in the literature for obtaining performance measures and developing staffing policies. However, most of this work has been from a pure probabilistic point of view and has not addressed issues of statistical inference. In this article, we consider Bayesian queuing models with impatient customers with particular emphasis on call center operations and discuss further extensions. We develop the details of Bayesian inference for queues with abandonment such as the M/M/s + M model (Erlang‐A). In doing so, we discuss the estimation of operating characteristics and its implications on staffing. We illustrate the implementation of the Bayesian models using actual arrival, service, and abandonment data from call centers. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

基于马尔可夫过程的介电函数理论研究

基于马尔可夫过程,研究电介质分别在阶跃电场、方波电场和交变电场条件下的极化过程,并给出了介电函数的一般表达式．     

A generalized assignment model for dynamic supply chain capacity planning

We consider a generalization of the well‐known generalized assignment problem (GAP) over discrete time periods encompassed within a finite planning horizon. The resulting model, MultiGAP, addresses the assignment of tasks to agents within each time period, with the attendant single‐period assignment costs and agent‐capacity constraint requirements, in conjunction with transition costs arising between any two consecutive periods in which a task is reassigned to a different agent. As is the case for its single‐period antecedent, MultiGAP offers a robust tool for modeling a wide range of capacity planning problems occurring within supply chain management. We provide two formulations for MultiGAP and establish that the second (alternative) formulation provides a tighter bound. We define a Lagrangian relaxation‐based heuristic as well as a branch‐and‐bound algorithm for MultiGAP. Computational experience with the heuristic and branch‐and‐bound algorithm on over 2500 test problems is reported. The Lagrangian heuristic consistently generates high‐quality and in many cases near‐optimal solutions. The branch‐and‐bound algorithm is also seen to constitute an effective means for solving to optimality MultiGAP problems of reasonable size. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

基于马尔可夫过程的武器系统相关失效分析

利用马尔可夫过程分别对共因失效和载荷共享失效两种相关失效的系统平均失效时间进行了建模分析。针对同时出现两种相关失效的武器系统进行了实例分析,并将结果和不考虑相关失效时的计算结果进行了对比,对相关失效分析在可靠性分析和评价中的重要作用进行了阐述。     

动态武器目标分配问题的马尔可夫性

动态武器目标分配(weapon target assignment,WTA)问题是军事运筹学研究的重要理论问题,也是作战指挥决策中迫切需要解决的现实问题。在对动态WTA问题进行描述分析的基础上,运用随机过程理论证明了动态WTA过程的马尔可夫性;给出了该马尔可夫决策过程的状态转移概率的解析表达式,并对其状态特点进行了简要分析。研究结果可以为动态WTA及相关问题的研究提供理论和方法依据。     

用户偏好提取MDP建模研究

将马尔可夫判决过程和智能强化学习算法相结合,给出了异构无线网络环境下用户业务偏好评估模型的技术框架。为动态环境下用户需求的感知、量化和适配特征的研究提供了基本的数学描述,对解决用户体验的评价问题和业务与业务环境的适配问题提供了新的研究思路。仿真结果表明所构建的MDP模型能够在多状态条件下学习用户偏好,根据用户需求智能选择业务。     

攻击机突防链型国土防空系统效能分析

封锁式防空和阻击式防空一般采用火力区相互接壤而形成链式防空,链式防空用于疆土防御.根据防空系统的任务和规模(国土防空、部队战场防空、海上舰队防空)以及入侵方式、武器性能特点的不同.基于随机理论建立了敌方采用同类武器组成链式防空体系,攻击机采用火力对抗条件下的国土突防模型.对基于随机理论的攻击机突防链型国土防空系统效能进行了一些假设和简化,建立了初步的效能模型,提供了一个分析的思路和方法.     

外场维护指挥控制系统可靠度模型

分析了影响外场指挥控制系统可靠性的主要因素,以指挥人员为主体,根据战时的实际,对指挥关系进行了重构,将串联指挥关系变为并联关系,通过利用马尔可夫链给出了指挥控制系统状态转移图,建立了计算外场指挥系统可靠性的数学模型。并且进一步给出了计算指挥控制系统的可靠性的方法。     

装备物资供应链构建初探

从供应链及供应链管理理论的思想角度出发 ,构建了装备物资供应链的结构模型 ,分析了其所具有的一些基本特征 ,为装备物资供应的胜利实施提供了一个新的思考方向