某大型超市电气消防安全设计

对大型超市进行合理的电气消防安全设计将直接关系人员的生命安全和国家的财产安全。以实际工程为研究对象,依据《民用建筑电气设计规范》、《火灾自动报警系统设计规范》等相关规范,结合工程实际,重点针对消防供配电系统、火灾探测器和手动报警按钮的布置以及消防设备的联动控制进行了设计。     

库存控制条件下弹药供应链稳定性研究

由于弹药供应链系统中存在牛鞭效应问题,为了减少牛鞭效应对弹药供应系统的影响,研究系统的稳定性,建立了一阶弹药供应链系统。分析了弹药供应链系统的构成,对系统进行了数学建模分析与仿真验证分析。分析得出,决策参数调整系数β对弹药供应链系统稳定性的影响明显,部队需求量变化及订货量决策参数安全系数α影响较弱。并得出系统稳定时或系统出现震荡、混沌现象时调整系数β的取值范围。     

用结构自适应前馈网络解算多目标导弹攻击区

多目标导弹攻击区的实时解算是机载多目标攻击武器系统得以技术实现的中心环节。阐述了“多目标导弹攻击区”的概念 ,探索了其解算的技术途径 ,提出了“实时、高精度和低存储”的解算要求。根据上述技术要求 ,设计了基于网络灵敏度统计分析的多层前馈网络结构自适应算法 ,以用于训练合适规模的多层前馈网络逼近器。在此基础上 ,进行了系统仿真研究 ,研究的结果表明了该方案的应用前景。     

空军武器装备体系作战效能分析

根据空军“攻防兼备”的作战要求 ,将空军的武器装备分为作战力量装备和保障力量装备 ,并按进攻和防守两种主要的作战样式对空军的武器装备体系进行了作战效能分析 ,探讨了分析空军武器装备体系作战效能的方法和思路 ,为建立空军武器装备体系作战效能评估仿真系统提供了基础。     

一种基于多目标优化的QoS路由交互式算法

为了满足通信网络中一些特定业务对于多个网络指标性能的同时要求 ,研究了一类基于多目标决策的QoS路由算法。通过选取带宽作为约束条件 ,把时延和丢失率作为优化目标 ,建立了QoS路由选择的多目标非线性整数规划模型 ,并给出了一种求解模型的交互式算法。该算法通过逐步调整目标函数的上界 ,压缩目标函数的搜索空间来满足决策者的要求和网络条件。实例计算结果表明了算法的可行性     

Dynamic pricing and inventory control with learning

Optimal operating policies and corresponding managerial insight are developed for the decision problem of coordinating supply and demand when (i) both supply and demand can be influenced by the decision maker and (ii) learning is pursued. In particular, we determine optimal stocking and pricing policies over time when a given market parameter of the demand process, though fixed, initially is unknown. Because of the initially unknown market parameter, the decision maker begins the problem horizon with a subjective probability distribution associated with demand. Learning occurs as the firm monitors the market's response to its decisions and then updates its characterization of the demand function. Of primary interest is the effect of censored data since a firm's observations often are restricted to sales. We find that the first‐period optimal selling price increases with the length of the problem horizon. However, for a given problem horizon, prices can rise or fall over time, depending on how the scale parameter influences demand. Further results include the characterization of the optimal stocking quantity decision and a computationally viable algorithm. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 303–325, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10013     

Inventory control under substitutable demand: A stochastic game application

Substitutable product inventory problem is analyzed using the concepts of stochastic game theory. It is assumed that there are two substitutable products that are sold by different retailers and the demand for each product is random. Game theoretic nature of this problem is the result of substitution between products. Since retailers compete for the substitutable demand, ordering decision of each retailer depends on the ordering decision of the other retailer. Under the discounted payoff criterion, this problem is formulated as a two‐person nonzero‐sum stochastic game. In the case of linear ordering cost, it is shown that there exists a Nash equilibrium characterized by a pair of stationary base stock strategies for the infinite horizon problem. This is the unique Nash equilibrium within the class of stationary base stock strategies. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 359–375, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10018     

A new importance sampling Monte Carlo method for a flow network reliability problem

The exact evaluation of the probability that the maximum st‐flow is greater than or equal to a fixed demand in a stochastic flow network is an NP‐hard problem. This limitation leads one to consider Monte Carlo alternatives. In this paper, we propose a new importance sampling Monte Carlo method. It is based on a recursive use of the state space decomposition methodology of Doulliez and Jamoulle during the simulation process. We show theoretically that the resulting estimator belongs to the variance‐reduction family and we give an upper bound on its variance. As shown by experimental tests, the new sampling principle offers, in many cases, substantial speedups with respect to a previous importance sampling based on the same decomposition procedure and its best performances are obtained when highly reliable networks are analyzed. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 204–228, 2002; DOI 10.1002/nav.10004     

多目标数据关联的神经网络方法

数据关联是多目标跟踪的关键问题。基于 Hopfield神经网络的 JPDA是解决这一关键问题的有效方法之一 ,但此方法的难点在于优化系数的整定。提出一种改进算法 ,用于解决优化系数在线自适应整定问题。首先重新构造了李雅普诺夫能量函数 ,接着引入变化的优化系数因子 ,并给出了优化系数求解的迭代公式 ;最后对已有和改进的算法进行了仿真研究。结果表明改进的方法和原有的方法相比 ,一方面具有在线整定优化系数的功能 ,另一方面可以获得和原有算法非常接近的估计误差。     

多传感器多目标定位与跟踪技术研究

针对炮兵打击目标的特性和获取目标信息所采用的侦察设施 ,研究了多传感器多目标定位和跟踪问题。在闭圆和聚类概念的基础上 ,提出了一种多传感器多目标融合算法 ,并给出了状态估计的最优解。仿真结果证明了这种算法的有效性。这一模型的物理实现正在进一步研究之中。