小户型公寓设计与分析

公寓房是我军住房保障体系的重要组成部分,其中又以小户型公寓房为主体,加强小户型公寓的设计研究对提高其保障效能具有现实意义。解读军队公寓住房建筑设计方案竞赛一等奖作品,指出小户型公寓采用一梯两户多层的形式在营造营区环境、降低建筑全寿命费用、改善室内舒适度等方面具有比较优势;应合理分配小户型公寓房面积,适当提高卫浴和厨房所占面积比例,控制客厅和卧室规模;应在门厅空间布局与卫浴空间分室设置、储藏空间多样化、布置多用途小空间、管井集中出户等方面提高设计的精细化程度。     

基于变异离散粒子群的协同空战攻击决策算法

为了提高智能协同空战攻击决策算法性能,将变异策略引入到DPSO(Discrete Particle Swarm Optimization)协同空战攻击决策算法中,提出了一种新的基于变异离散粒子群(Mutation Discrete Particle Swarm Optimization,MDPSO)的协同空战攻击决策算法。基于典型空战想定背景,仿真验证了算法的有效性。采用对比实验方法,基于准确性、可靠性和快速性等关键性能指标,分析比较了基于MDPSO协同空战攻击决策算法与多种智能决策算法,验证了基于MDPSO的协同空战攻击决策算法有着较好的综合性能。     

协同OFDM放大前传空时编码系统中的功率分配

针对由源节点和单个中继节点形成的协同正交频分复用( OFDM) Alamouti空时块码系统,分析了放大前传(AF)模式下的系统容量,给出了解析表达式.考虑节点功率独立约束的应用场景,提出了分步迭代的功率分配算法( SIPAA)来提高系统容量.该算法的核心思想是在每次迭代中,分步对源和中继节点分别进行注水功率分配,注水...     

改进的TOPSIS法在雷达干扰资源分配中的应用

对雷达进行侦查是干扰雷达的前提,由于侦查无法得到精确的实际雷达工作参数,而只能得到一个工作参数区间,因此属性值为确定值的多属性决策方法是不适用的.从多个属性出发,提出改进的基于逼近理想解排序的TOPSIS法,针对属性权重信息不完全且属性值为区间数的特征,将多属性决策问题运用到雷达干扰资源分配中来,对雷达干扰资源进行优选配置,通过多个无线传感器干扰节点协同干扰,使其达到最佳的干扰效果.     

防空系统目标威胁评估与火力分配模型

首先运用层次分析法建立了防空系统对空袭目标价值评估模型的层次结构,并获得空袭目标的价值权重系数。其次,在综合考虑目标价值权重的基础上,运用模糊决策的方法推导出防空系统目标威胁综合评估数学模型。最后运用军事运筹学0-1整数规划的方法,给出了防空系统目标优化火力分配0-1整数规划数学模型。     

基于遗传算法的涡轮增压器叶轮优化设计

提出了一种基于遗传优化理论的涡轮增压器叶轮的优化设计方法,论述了以涡轮增压器叶轮能量损失最小为目标函数,以叶轮叶片进口角、进口直径、进口宽度、出口直径、叶片数、出口角为设计变量的涡轮增压器叶轮的优化设计模型及优化计算的方法,数值计算表明,这种算法可以方便地求得具有最小涡轮损失的涡轮叶形参数.     

Optimal material control in an assembly system with component commonality

Allocation of scarce common components to finished product orders is central to the performance of assembly systems. Analysis of these systems is complex, however, when the product master schedule is subject to uncertainty. In this paper, we analyze the cost—service performance of a component inventory system with correlated finished product demands, where component allocation is based on a fair shares method. Such issuing policies are used commonly in practice. We quantify the impact of component stocking policies on finished product delays due to component shortages and on product order completion rates. These results are used to determine optimal base stock levels for components, subject to constraints on finished product service (order completion rates). Our methodology can help managers of assembly systems to (1) understand the impact of their inventory management decisions on customer service, (2) achieve cost reductions by optimizing their inventory investments, and (3) evaluate supplier performance and negotiate contracts by quantifying the effect of delivery lead times on costs and customer service. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48:409–429, 2001     

防空导弹武器系统目标分配的多种算法

叙述了防空导弹武器系统目标分配的一般数学模型。在此基础上,建立了防空导弹的5种目标分配数学优化算法,并讨论了数学模型的求解问题。最后,对这5种数学优化算法进行了比较。     

多级可修备件库存的生灭过程建模与优化

针对VARI-METRIC模型在低可用度下结果不准确的问题,建立基于生灭过程的任意等级、任意层级可修件库存优化模型。通过对各级站点、各类备件需求率与到达率的预测,对每个部件建立其生灭过程模型,并提出基于生灭过程的装备可用度计算方法。以整个保障系统的装备可用度为约束指标,以备件总购置费最低为目标,利用边际算法得到最优备件配置方案,并建立仿真模型对所得优化方案进行评估与调整。结合算例,以仿真结果作为检验标准,选取权威的VMETRIC软件与该解析模型在优化性能、计算精度及适用性上进行对比和说明。结果表明,无论是解析模型还是VMETRIC软件,均存在一定的适用范围,而采用解析与仿真相结合的方法无疑具有更强的适应性。     

Optimal service and arrival rates in Jackson queueing networks

In this paper we present an algorithm for solving a class of queueing network design problems. Specifically, we focus on determining both service and arrival rates in an open Jackson network of queueing stations. This class of problems has been widely studied and used in a variety of applications, but not well solved due to the difficulty of the resulting optimization problems. As an example, consider the classic application in computer network design which involves determining the minimum cost line capacities and flow assignments while satisfying a queueing performance measure such as an upper limit on transmission delay. Other application areas requiring the selection of both service and arrival rates in a network of queues include the design of communication, manufacturing, and health care systems. These applications yield optimization problems that are difficult to solve because typically they are nonconvex, which means they may have many locally optimal solutions that are not necessarily globally optimal. Therefore, to obtain a globally optimal solution, we develop an efficient branch and bound algorithm that takes advantage of the problem structure. Computational testing on randomly generated problems and actual problems from a health care organization indicate that the algorithm is able to solve realistic sized problems in reasonable computing time on a laptop computer. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 1–17, 2000