基于定期维修的k/N系统维修渠道优化模型

针对定期维修策略下的k/N系统维修渠道的配置问题,建立了多类故障单元批量定期送修的维修渠道优化模型。首先,给出了定期维修策略下的k/N系统工作流程和故障单元维修流程;然后,根据故障单元批量定期送修的特点,提出了Dξ/M/c排队模型,并对关键输入参数进行了修正与计算,对排队系统的稳态概率进行了求解;接着,建立了多类故障单元同时送修的维修渠道优化模型,通过将多类顾客源多服务台排队系统转化为单类顾客源多服务台排队系统,对优化模型进行了求解;最后,通过算例仿真与分析,对模型进行了验证。结果表明,该模型能够为k/N系统维修渠道数量的确定提供理论依据,对部队维修资源的合理配置具有一定的指导意义。     

战术级维修人员分配研究

首先对战时战术级维修力量分配问题进行描述,分析运用排队论解决本问题的可行性,确定建模思路;基于排队论建立战时战术级维修力量分配模型,使装备平均维修时间最短,解决了战术级维修力量分配问题。     

基于排队论的海量信息存储配置优化

本文为了探讨海量信息存储的配置问题,首先对几种主要的网络存储构架进行比较,利用排队理论对iSCSI-SAN存储中的排队过程进行分析和数学建模,用带宽比例求解方法,即系统负载所需的带宽与阵列所能提供的带宽的比例,来确定该存储配置是否能满足用户的需求,据此可以组成优化配置。     

优化参数配置提高WCDMA网络无线接通率

通过优化相关参数配置,有效地提高了WCDMA网络的RRC建立成功率,改善了无线接通率指标。从接入过程的不同方面进行了分析,并提出相应的解决方法,对于处理类似问题具有一定的参考价值。     

基于排队论的故障预处理值班人员优化配置

伴随着集中故障管理项目的推进,为了应对故障配合电话接通率和服务质量等需求,集中故障人工配合方案应运而生。与此同时,故障预处理平台值班人员配置问题随之出现。本文就是利用排队论的相关知识,分析故障预处理平台故障处理配合过程的特点,并建立了该系统的M/M/C/∞/∞/FIFO模型,确定了参数指标和性能指标。通过对通话详情的统计,分析出值班人员进行故障处理配合的工作状况,并对值班人员数量的安排进行了优化分析,得出了合理分配值班人员的方法和依据。     

谈乡镇卫星电视接收站的优化配置

谈乡镇卫星电视接收站的优化配置□黄奕铭（南京炮兵学院电教中心２１１１３２）近年来，随着乡镇有线电视的蓬勃发展，卫星电视以其覆盖面广，传送质量好，节目套数多等优点，已成为乡镇有线电视的主要节目源。但乡镇有线电视投资少，条件差，技术力量薄弱，因此，必须结...     

备件优化配置模型研究

为增加备件配置的科学性,达到在确保网络可靠性的前提下,降低备件配置所占用资金及提高备件资源利用率的目的,对备件优化配置方法进行了研究.分析了影响备件配置的各种因素,建立了网络部件损坏和维修返回事件的数学模型.对于现网中数量较多的设备类型,提出了基于排队服务理论的大数量备件服务模型.对于现网中数量较少的设备类型,提出了基于可靠性理论的小数量备件服务模型.分别对两类模型进行了理论分析,得到了满足该两种情况下的备件优化配置计算方法.介绍了基于该方法的优化配置系统在中国联通的全国骨干传送网中部署使用的情况.     

自己动手进行多重优化配置

<正> 计算机系统设置是通过CONFIG.SYS和AUTOEX-EC.BAT这两个文件实现的。由于电脑软件、硬件以及应用程序的不同,所需要配置的信息也有差异。因此,电脑在实际使用时一般要经常修改上述两个配置文件,以满足某种软硬件的配置要求。MS-DOS6.0以上版本的操作系统允许用户对CONFIG.SYS及AUTOEXEC.BAT进行多重功能设置,且提供内存系统的优化功能,这样在运行不同要求配     

美国频谱资源优化配置探析

介绍了美国对原广播电视视频段和原联邦政府各机构使用频谱资源的回收与重置情况,通过研究美国频谱资源的优化配置,以期对我国无线电频谱统等规划提供参.     

网络备用容量优化的一种数学模型

本文研究了ＳＤＨ通信网的保护问题。当故障发生时，必须找到一些路由用于建立足够的恢复通道。同时，在建立一个通信网络时，希望在满足一定保护要求的前提下使用最少的备用资源。解决这个问题的这一步是提出一个数学模型。这也是最困难和最重要的一步。一旦建立了一个数学模型，我们就可以用某种数学上的算法来解决它了。     

An optimal maintenance model using a number of different actions

In this paper, we study an optimal maintenance model. The state of a system is determined by the distribution of its operating time. Whenever the system fails, a number of actions can be chosen, including the repair actions, the replacement actions and the action of discarding the system. The objective of this paper is to determine an optimal policy which maximizes the expected total discounted reward. By using the semi-Markov decision process approach, the method of successive approximations is suggested for determining the optimal reward function and the corresponding optimal policy.     

Evaluation of average maintenance cost for imperfect-repair model

The imperfect-repair model considers units which are either perfectly-repaired or minimally-repaired, with known, fixed probabilities. Minimal repair is defined, roughly, as returning the item to the population's average state at the failure time. The average cost of maintaining the unit under this model is studied by assuming fixed amounts of cost for perfect and minimal repairs when failed. The authors' measure of such maintenance cost is an average cost per unit-time over an infinite time span. To obtain this average cost, they use the expressions for average numbers of perfect and minimal repairs under this model. They prove the few theorems necessary to derive the formulae for the average cost per unit-time. The results are applied to some examples     

A maintenance model for two-unit redundant system

In this paper, a maintenance model for two-unit redundant system with one repairman is studied. At the beginning, unit 1 is operating, unit 2 is the standby unit. The costs include the operating reward, repair cost and replacement cost, besides, a penalty cost is incurred if the system breaks down. Two kinds of replacement policy, based on the number of failures for two units and the working age, respectively are used. The long-run average cost per unit time for each kind of replacement policy is derived. Also, a particular model in which the system is deteriorative, two units are identical and the penalty cost rate is high, is thoroughly studied.     

The effect of model uncertainty on maintenance optimization

Much operational reliability data available, e.g., in the nuclear industry, is heavily right-censored by preventive maintenance. The common methods for dealing with right-censored data (total time on test statistic, Kaplan-Meier estimator, adjusted rank methods) assume the s-independent competing-risk model for the underlying failure process and the censoring process, even though there are, many s-dependent competing-risk models that can also interpret the data. It is not possible to identify the "correct" competing risk model from censored data. A reasonable question is whether this model uncertainty is of practical importance. This paper considers the impact of this model-uncertainty on maintenance optimization, and shows that it can be substantial. Three competing-risk model classes are presented which can be used to model the data, and determine an optimal maintenance policy. Given these models, then consider the error that is made when optimizing costs using the wrong model. Model uncertainty can be expressed in terms of the "dependence between competing risks" which can be quantified by expert judgment. This enables reformulating the maintenance optimization problem to account for model uncertainty.     

变电设备差异化运维策略优化设计

基于信息化时代背景下,随着一系列先进技术手段的诞生与普及性运用,促使电力设备状态评价与风险评估体系越加完善,进而为变电运行人员实现对设备运行状态的有效掌握奠定了基础.     

A generic model of equipment availability under imperfect maintenance

This paper explores the impact of imperfect repair on the availability of repairable equipment. Kijima's first virtual age model is used to describe the imperfect repair process. Due to the complexity of the underlying assumptions of this model, we are unable to derive a closed-form equation for availability. Therefore, simulation modeling & analysis are used to evaluate equipment availability. Based on initial availability plots, a generic availability function is proposed. A 2/sup 3/ factorial experiment is performed to evaluate the accuracy of this model. The maximum absolute error between the simulation output, and the corresponding values of the availability function is 3.82%. This indicates that our proposed function provides a reasonable approximation of equipment availability, which simplifies meaningful analysis for the unit. Therefore, a method is defined for determining optimum equipment replacement intervals based on average cost. Next, meta-models are developed to convert equipment reliability & maintainability parameters into the coefficients of the availability model. We expand on our initial experiment using a circumscribed central composite experimental design. We evaluate the accuracy of the meta-models for the 15 experiments & 50 random experiments within the design space. For the 50 new experiments, we compare the replacement policy obtained from analysis of the meta-model to the policy obtained directly from the simulation output. The average increase in cost resulting from the sub-optimal replacement policy is only 0.10%. Therefore, we conclude that the meta-models are robust, and provide good estimates of the parameters of our proposed availability function. By doing this, we eliminate the need to perform simulation to obtain the parameters of the availability model.     

A failure-repair model with minimal and major maintenance

A Markov model for a continuously operating service device whose condition deteriorates with time in service is proposed. The model incorporates deterioration and Poisson failures, minimal repair, periodic minimal maintenance, and major maintenance after a given number of minimal maintenances. An exact recursive algorithm computes the steady-state probabilities of the device. A cost function is defined using different cost rates for the different types of outages. Based on minimal unavailability or minimal costs, optimal solutions of the model are derived. Major maintenance is seldom beneficial if optimal maintenance intervals are used. If a maintenance policy is based on nonoptical intervals between maintenances, periodic major maintenance can reduce costs     

A VLSI model for residue number system architectures

Combining the Residue Number System as a computational tool and VLSI as a fabrication medium promises to provide modular and cost efficient implementation of many digital signal processing algorithms. In this paper, a memory model has been developed. It is a low level model, which is used to derive relationships between the size of each modulus (in the chosen number system), and both chip area and time required for implementing the corresponding look-up tables. The memory model allows the selection of the most efficient layout for memories which do not have power of two dimensions. A set of multi-look-up table modules has been proposed as building block units for implementing digital signal processing algorithms. A procedure has been developed to optimize the area and time of those modules.     

多光子反Jaynes-Cummings模型中纠缠原子的布局数反转演化

利用多光子反Jaynes-Cummings模型研究了单模相干光场与两个全同的纠缠二能级原子相互作用时纠缠原子的布局数演化,并讨论相干光场的平均光子数及跃迁光子数对纠缠原子布局数产生的影响。结果表明：随着相干光场平均光子数的增加纠缠二能级原子处于激发态和基态的几率差减小,布局数的振荡曲线整体上移; 随着跃迁光子数的增加纠缠二能级原子处于激发态和基态的几率差增大, 振荡曲线整体下移。     

基于mRMR-BP算法的辛烷值损失预测模型研究

化工过程建模一般通过数据关联或机理建模的方法来实现,但由于炼油工艺过程的复杂性以及设备的多样性,其操作变量之间具有高度非线性和相互强耦联的关系.在传统的数据关联模型中,变量相对较少、机理建模对原料的分析要求较高,对过程优化的响应不及时,效果并不理想.本文为了降低模型求解的复杂性,使用互信息法和mRMR算法,对367个变...