A bivariate optimal replacement policy for a cold standby repairable system with repair priority

In this article, an optimal replacement policy for a cold standby repairable system consisting of two dissimilar components with repair priority is studied. Assume that both Components 1 and 2, after repair, are not as good as new, and the main component (Component 1) has repair priority. Both the sequence of working times and that of the components'repair times are generated by geometric processes. We consider a bivariate replacement policy (T,N) in which the system is replaced when either cumulative working time of Component 1 reaches T, or the number of failures of Component 1 reaches N, whichever occurs first. The problem is to determine the optimal replacement policy (T,N)* such that the long run average loss per unit time (or simply the average loss rate) of the system is minimized. An explicit expression of this rate is derived, and then optimal policy (T,N)* can be numerically determined through a two‐dimensional‐search procedure. A numerical example is given to illustrate the model's applicability and procedure, and to illustrate some properties of the optimal solution. We also show that if replacements are made solely on the basis of the number of failures N, or solely on the basis of the cumulative working time T, the former class of policies performs better than the latter, albeit only under some mild conditions. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

基于目标威胁度的相控阵雷达自适应调度方法

对时间资源的合理安排是相控阵雷达发挥自身优势的关键。将目标威胁度引入调度算法中,与工作方式和任务截止期共同进行综合优先级规划。通过构建目标威胁度的量化模型,使雷达在调度跟踪任务时依目标威胁度大小分配时间。提出了修正价值率和执行威胁率的概念,完善了性能评估指标。通过仿真,全面评价了新算法性能,验证了引入目标威胁度的合理性。结果表明,新算法可以有效提升相控阵雷达对高威胁度目标的处理能力。     

Discrete‐time analysis of MAP/PH/1 multiclass general preemptive priority queue

We use the matrix‐geometric method to study the MAP/PH/1 general preemptive priority queue with a multiple class of jobs. A procedure for obtaining the block matrices representing the transition matrix P is presented. We show that the special upper triangular structure of the matrix R obtained by Miller [Computation of steady‐state probabilities for M/M/1 priority queues, Oper Res 29(5) (1981), 945–958] can be extended to an upper triangular block structure. Moreover, the subblock matrices of matrix R also have such a structure. With this special structure, we develop a procedure to compute the matrix R. After obtaining the stationary distribution of the system, we study two primary performance indices, namely, the distributions of the number of jobs of each type in the system and their waiting times. Although most of our analysis is carried out for the case of K = 3, the developed approach is general enough to study the other cases (K ≥ 4). © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 662–682, 2003.     

Optimal replacement of continuously degrading systems in partially observed environments

Motivated by wind energy applications, we consider the problem of optimally replacing a stochastically degrading component that resides and operates in a partially observable environment. The component's rate of degradation is modulated by the stochastic environment process, and the component fails when it is accumulated degradation first reaches a fixed threshold. Assuming periodic inspection of the component, the objective is to minimize the long‐run average cost per unit time of performing preventive and reactive replacements for two distinct cases. The first case examines instantaneous replacements and fixed costs, while the second considers time‐consuming replacements and revenue losses accrued during periods of unavailability. Formulated and solved are mixed state space, partially observable Markov decision process models, both of which reveal the optimality of environment‐dependent threshold policies with respect to the component's cumulative degradation level. Additionally, it is shown that for each degradation value, a threshold policy with respect to the environment belief state is optimal if the environment alternates between two states. The threshold policies are illustrated by way of numerical examples using both synthetic and real wind turbine data. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 395–415, 2015     

面向访问模式的多核末级Cache优化方法

多核处理器架构已经成为当前处理器的主流趋势,应用程序中访问模式的多样性给多核处理器的末级Cache带来了许多挑战。提出了访问模式的多核末级Cache优化方法,它包含"可配置的共享私有Cache划分"、"可配置的旁路Cache策略"和"优先权替换策略"三个协同递进的层次。通过使用该方法,程序员能够灵活地改变末级Cache执行行为,从而高效地适应应用程序访问模式的变化。实验结果表明,提出的方法能够显著降低末级Cache的缺失率,进而提高系统的整体性能。     

基于评估的任务间隔期维修任务选择方法

针对任务间隔期维修任务的选择问题,提出了求解该问题的方法。首先,给出了维修任务优先级评估指标,以及修理有效性评估指标;然后,提出了AHP-熵-DEA-TOPSIS方法,用来确定维修任务的优先级,以及修理有效性;接着建立基于维修效果的数学规划模型,其目标是使维修方案的加权有效性总和在满足维修资源约束条件下最大化。最后,应用该方法对具体示例进行了求解,验证了方法的有效性和可行性。分析表明所求得的维修任务选择方案能够充分利用各种信息,具有较强的可信性与实用性,有助于维修管理人员对维修任务选择进行优化。     

求解武器目标分配问题的改进粒子群算法

在建立多种类型武器目标分配模型的基础上,提出了一种求解该模型的改进粒子群算法。首先,定义粒子聚焦距离变化率,使惯性权重依据聚焦距离变化率自适应调整;其次,采用速度最大值线性递减的策略平衡算法收敛精度与全局寻优能力之间的矛盾;最后,粒子替换策略使算法改善了因自适应惯性权重的引入而造成收敛速度变慢的问题。仿真结果表明,提出模型和算法合理有效,算法收敛快,适合求解各种种群规模的武器目标分配问题。     

Context 的非单调推理

基于文［１］定义的ｃｏｎｔｅｘｔ逻辑ＣＬ,本文分别引入限制理论和缺省理论到ｃｏｎ－ｔｅｘｔ推理中,给出有关的定义和定理。     

Priority queue with customer upgrades

This article is concerned with a general multi‐class multi‐server priority queueing system with customer priority upgrades. The queueing system has various applications in inventory control, call centers operations, and health care management. Through a novel design of Lyapunov functions, and using matrix‐analytic methods, sufficient conditions for the queueing system to be stable or instable are obtained. Bounds on the queue length process are obtained by a sample path method, with the help of an auxiliary queueing system. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

The parallel replacement problem with demand and capital budgeting constraints

A generalized parallel replacement problem is considered with both fixed and variable replacement costs, capital budgeting, and demand constraints. The demand constraints specify that a number of assets, which may vary over time, are required each period over a finite horizon. A deterministic, integer programming formulation is presented as replacement decisions must be integer. However, the linear programming relaxation is shown to have integer extreme points if the economies of scale binary variables are fixed. This allows for the efficient computation of large parallel replacement problems as only a limited number of 0–1 variables are required. Examples are presented to provide insight into replacement rules, such as the “no‐splitting‐rule” from previous research, under various demand scenarios. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 40–56, 2000