基于遗传算法的雷达功能板备件优化模型

通过分析雷达装备的维修方式和可用度，建立了雷达装备的功能板（印制版）随机备件优化模型，结合遗传算法解优化问题的特点，将遗传算法引入到求解备件优化问题中来，有效地解决了这一复杂的备件优化问题，保证了雷达装备具有较高的可用度。     

基于遗传算法的弹药装备备件优化模型研究

结合当前弹药装备备件优化配置的工程需求,建立了基于遗传算法的备件优化模型。在弹药装备战备完好率和费用的共同约束下,利用遗传算法收敛速度快、全局寻优能力强、编程实现简单等特点,实现了对该模型的求解,得到了弹药装备备件的最优配置。最后,以某弹药装备为案例进行了分析,结果表明,遗传算法能有效地解决弹药装备备件的优化问题。     

雷达兵指挥自动化系统装备备件优化模型研究

雷达兵指挥自动化系统装备备件费用直接影响系统备件保障概率,而备件保障概率又影响到维修保障及系统的战备完好性,因而如何利用好有限的备件费用,得到较大的战备完好率是一个重要的研究课题.建立了系统战备完好率与备件费用之间的函数关系,并利用遗传算法对系统备件优化模型求解进行了阐述.     

某火控系统备件需求计算方法研究

研究装备备件需求计算方法,为某自行火炮火控系统备件保障提供决策依据。通过研究备件在装备保障中的重要性,分析了影响装备备件需求的因素,讨论了基于贝叶斯的某自行火炮火控系统的备件需求计算法。从而得出了基于贝叶斯的某自行火炮火控系统备件需求预测计算模型。对于随机波动、变化相对稳定的指标,用贝叶斯模型预测是比较精确的,在实际工作中具有可行性。     

基于备件缺货率的多级库存优化研究

部队备件管理库存问题,是一个十分重要和复杂的问题。从供应链的角度出发对部队的备件库存管理进行了探讨和论述,分析了部队备件库存管理的特点。在此基础上,考虑到实际情况中部队仓库库址分散,通过分析备件在补货过程中发生的各种相关费用和备件缺货率,建立了以一个补货周期内供应链的补货总成本最小为优化目标的补货模型,并给出求解方法。     

雷达可修复备件优化配置研究

备件保障是提高装备的战备完好性和降低寿命周期费用的重要研究领域.文中研究了可修复备件保障建模方法及应用,基于METRIC模型基本理论,并结合雷达装备备件保障现状,建立了雷达可修复备件优化配置模型.模型采用备件期望短缺数作为模型的优化目标,运用边际效能法优化备件配置,并结合实例进行了应用.     

基于可靠性约束的网络多目标满意优化

利用满意优化方法综合考虑网络可靠性和网络费用,以此来建立网络拓扑结构设计的数学模型,并描述了用遗传算法求解该问题的方法。满意优化与遗传算法相结合成功解决了网络高可靠性和低费用之间的矛盾。最后,通过与一般优化方法结果相比较来说明算法的有效性,给出其仿真的结果。     

对未来航空火控系统发展的思考

简要阐述未来战斗机火控系统发展方向问题,包括树立大火控系统观念,建立总体优化火控系统以下一代战斗机火控体应当重点控制的几个问题。     

雷达装备可修复备件三级库存优化仿真

针对雷达装备器材供应保障中可修复备件配置问题,在分析三级保障结构下可修复备件运转流程的基础上,构建了可修复备件三级供应保障结构下库存优化模型。模型采用基层级供应可用度作为优化目标,以备件订购费用作为约束条件,运用边际分析法优化可修复备件三级库存配置,实现了在有限购置费用约束条件下的基层级供应可用度最大化。最后,通过实例对三级库存模型进行了仿真分析,并评估了中继级维修时间、基地级补给时间等因素对基层级供应可用度的影响,仿真结果可为雷达装备可修复备件合理配置提供参考。     

雷达随机备件品种与数量的工程估算方法

提出雷达以功能板（印制板）为随机备件时，根据给定的备件保障水平，依据功能板的故障率和修复周期，确定随机备件品种与数量的工程估算方法     

Approximating optimal spare capacity allocation by successive survivable routing

The design of survivable mesh based communication networks has received considerable attention in recent years. One task is to route backup paths and allocate spare capacity in the network to guarantee seamless communications services survivable to a set of failure scenarios. This is a complex multi-constraint optimization problem, called the spare capacity allocation (SCA) problem. This paper unravels the SCA problem structure using a matrix-based model, and develops a fast and efficient approximation algorithm, termed successive survivable routing (SSR). First, per-flow spare capacity sharing is captured by a spare provision matrix (SPM) method. The SPM matrix has a dimension the number of failure scenarios by the number of links. It is used by each demand to route the backup path and share spare capacity with other backup paths. Next, based on a special link metric calculated from SPM, SSR iteratively routes/updates backup paths in order to minimize the cost of total spare capacity. A backup path can be further updated as long as it is not carrying any traffic. Furthermore, the SPM method and SSR algorithm are generalized from protecting all single link failures to any arbitrary link failures such as those generated by Shared Risk Link Groups or all single node failures. Numerical results comparing several SCA algorithms show that SSR has the best trade-off between solution optimality and computation speed.     

(s,Q) Spare Parts Provisioning Strategy for Periodically Replaced Systems

A joint preventive maintenance and spare parts provisioning strategy is suggested for a failure prone system. Replacements are carried-out at failure, if spare parts are available, and at spare parts replenishment delivery instants. Spare parts are provisioned according to an (s, Q) control policy. The ordering parameters, and preventive maintenance interval are derived from a mathematical model which aims at maximizing the system's availability under a budget constraint. The model takes into account the system lifetime distribution, the preventive and corrective maintenance costs and durations, as well as the total spare parts inventory management cost. Unlike classical inventory management models, the s-expected total cost is derived using the system lifetime distribution. Because each demand for spare parts is triggered by failure, the probabilities of shortage, and surplus will be evaluated based on the system failure distribution rather than the demand distribution during the lead-time. Numerical results have been obtained for an illustrative example.     

面向任务的备件携行量仿真优化方法

在多阶段任务系统中，可修部件的寿命服从一般分布、维修时间也服从一般分布的备件携行量优化问题很难利用解析方法来解决。采用仿真的方法，建立可修部件寿命和维修时间均服从一般分布的多阶段任务系统的仿真模型，给出了最优备件携行量的仿真计算方法，讨论了如何确定维修组的数量。并且通过实例检验了这种仿真方法的适用性。最后利用一个指数分布实例对解析方法和仿真方法计算出的结果进行比较，从而对所提出的仿真方法进行了检验。     

Spare Capacity Allocation in Two-Layer Networks

In this paper we consider the problem of provisioning spare capacity in two-layer backbone networks using shared backup path protection. First, two spare capacity allocation (SCA) optimization problems are formulated as integer linear programming (ILP) models for the cases of protection at the top layer against failures at the bottom layer. The first model captures failure propagation using overlay information between two layers for backup paths to meet diversity requirements. The second model improves bandwidth efficiency by moving spare capacity sharing from the top layer to the bottom layer. This exposes a tradeoff between bandwidth efficiency and extra cross-layer operation. Next, the SCA model for common pool protection is developed to allow spare capacity sharing between two layers. Our previous SCA heuristic technique, successive survivable routing (SSR) is extended for these optimization problems. Numerical results for a variety of networks indicate that the common pool protection is attractive to enhance bandwidth efficiency without loss of survivability and that the SSR heuristic quickly results in near optimal solutions     

Optimizing Embedded Passive Content in Printed Circuit Boards

A genetic algorithm's optimization approach is used in conjunction with a size/cost model to study the optimum mix of passives (resistors and capacitors) to embed within a printed circuit board on an application-specific basis. Using the models and solution approach developed in this paper, the effect of board size on the optimum embedded passive solution (minimum cost solution) is studied, and an assessment of whether better system solutions can be found by varying or constraining the size of the board using several different criteria has been performed. Example optimization results for a GSM mobile phone are presented. The analysis has shown that the system size limitation when embedded passives are used is not only dependent on the quantity, type, and electrical properties (capacitance and resistance) of the embeddable components, but is also very sensitive to layout specifications and the placement of the nonembeddable parts.     

一种异厂家间OA盘临时替代的方案

高速率波分系统在电信运营商中大量使用,在很多情况下,关键机盘如光放大器(OA)的故障,会造成大量业务受损,此时采用备品备件替换故障盘是最佳选择。但某些情况下,故障点缺乏相应备件,但有其他厂家的类似备件。如何利用现有资源,快速恢复业务,本文就此问题进行了探讨。     

k-out-of-m system availability with minimum-costallocation spares

An optimization method for determining the number of spare units that should be allocated to a k-out-of-m system to minimize the system-spares cost yet attain the specified system availability is presented. The objective function for optimization is a nonlinear integer type. The optimization method is a variation of the simplex search technique used for continuous functions. The optimization problem is cast in a form that minimizes the system-spares cost, with the required system availability as an inequality constraint. Results obtained by using the proposed optimization technique, as well as the computation time required for optimization, are compared to those for methods developed specifically for dealing with nonlinear integer problems. The method is simple, easy to implement, and yet very effective in dealing with the spare allocation problem for k-out-of-m:F systems