基于Stateflow的排队系统仿真方法

论述了排队系统与Stateflow相关概念,利用有限状态机理论与面向对象编程思想,提出了建立基于Stateflow排队系统模型的分析步骤,阐述了应用Stateflow对排队系统进行建模与仿真的方法,使用Stateflow对M／M／1／∞／∞／FIFO类型排队系统进行了具体的建模与仿真。仿真结果表明,基于Stateflow的模型与仿真能够有效地描述排队系统的统计特性,并具有可视化、流程化和层次化的特点。     

Heuristics for the multi‐resource generalized assignment problem

The well‐known generalized assignment problem (GAP) involves the identification of a minimum‐cost assignment of tasks to agents when each agent is constrained by a resource in limited supply. The multi‐resource generalized assignment problem (MRGAP) is the generalization of the GAP in which there are a number of different potentially constraining resources associated with each agent. This paper explores heuristic procedures for the MRGAP. We first define a three‐phase heuristic which seeks to construct a feasible solution to MRGAP and then systematically attempts to improve the solution. We then propose a modification of the heuristic for the MRGAP defined previously by Gavish and Pirkul. The third procedure is a hybrid heuristic that combines the first two heuristics, thus capturing their relative strengths. We discuss extensive computational experience with the heuristics. The hybrid procedure is seen to be extremely effective in solving MRGAPs, generating feasible solutions to more than 99% of the test problems and consistently producing near‐optimal solutions. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 468–483, 2001     

Bayesian inference based on partial monitoring of components with applications to preventive system maintenance

Consider a binary, monotone system of n components. The assessment of the parameter vector, θ, of the joint distribution of the lifetimes of the components and hence of the reliability of the system is often difficult due to scarcity of data. It is therefore important to make use of all information in an efficient way. For instance, prior knowledge is often of importance and can indeed conveniently be incorporated by the Bayesian approach. It may also be important to continuously extract information from a system currently in operation. This may be useful both for decisions concerning the system in operation as well as for decisions improving the components or changing the design of similar new systems. As in Meilijson [12], life‐monitoring of some components and conditional life‐monitoring of some others is considered. In addition to data arising from this monitoring scheme, so‐called autopsy data are observed, if not censored. The probabilistic structure underlying this kind of data is described, and basic likelihood formulae are arrived at. A thorough discussion of an important aspect of this probabilistic structure, the inspection strategy, is given. Based on a version of this strategy a procedure for preventive system maintenance is developed and a detailed application to a network system presented. All the way a Bayesian approach to estimation of θ is applied. For the special case where components are conditionally independent given θ with exponentially distributed lifetimes it is shown that the weighted sum of products of generalized gamma distributions, as introduced in Gåsemyr and Natvig [7], is the conjugate prior for θ. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 551–577, 2001.     

A risk function for the stochastic modeling of electric capacity expansion

We present a stochastic optimization model for planning capacity expansion under capacity deterioration and demand uncertainty. The paper focuses on the electric sector, although the methodology can be used in other applications. The goals of the model are deciding which energy types must be installed, and when. Another goal is providing an initial generation plan for short periods of the planning horizon that might be adequately modified in real time assuming penalties in the operation cost. Uncertainty is modeled under the assumption that the demand is a random vector. The cost of the risk associated with decisions that may need some tuning in the future is included in the objective function. The proposed scheme to solve the nonlinear stochastic optimization model is Generalized Benders' decomposition. We also exploit the Benders' subproblem structure to solve it efficiently. Computational results for moderate‐size problems are presented along with comparison to a general‐purpose nonlinear optimization package. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48:662–683, 2001     

区间分解组合迭代算法用于非确定结构系统的静力区间分析

对于结构参数向量界限绝对离差较大的非确定结构系统,迭代计算收敛条件难以满足,修正迭代算法不能直接用于其区间有限元静力控制方程的求解。采用区问分解组合求解策略,考虑区间矩阵、向量元素间的相关性,直接对结构参数区间进行区间分解,将非确定结构系统区间有限元控制方程的求解转化为若干个子区间有限元静力控制方程的修正迭代求解,提出了一种求解过程可逆的区间分解组合迭代算法,用于结构参数向量界限绝对离差较大的非确定结构系统的静力区间分析。算例结果表明,该方法是有效的。     

解坦克分队武器-目标分配问题的小生境遗传算法

为快速求解坦克分队武器-目标分配（Weapon-Target Assignment,WTA）模型,对基本遗传算法的关键步骤进行改进,设计了独特的基于火力单元排序的战术种群初始化策略,引入小生境共享函数和参数自适应机制,完成了基于小生境自适应改进遗传算法的设计与实现。最后进行了仿真试验,试验结果表现出了良好的收敛效果。     

战时不完全信息战术导弹需求量预测方法

针对传统方法难以实现战时信息不完备条件下导弹需求量预测的问题,提出了一种基于粗糙集的战术导弹需求量预测方法。在对战术导弹需求量影响因素分析的基础上,建立了战术导弹需求量预测不完备决策信息表。利用相容关系对不完备决策信息表中对象分类,并采用差别函数方法求解各对象的相对约简,从而获取战术导弹需求量的最优广义规则集。算例验证了方法的有效性。     

基于形态滤波的漏磁信号基线漂移在线处理

为了实现快速漏磁检测,采用形态滤波的方法对漏磁信号的基线漂移进行在线处理．首先,运用Maragos类型形态滤波器,选择平面结构元素作为最佳形态滤波形式,并通过实验得到最佳结构元素选取标准;然后,利用该滤波器和小波分解的方法分别对仿真信号和采集到的漏磁信号进行基线漂移的处理．结果表明：形态滤波的方法能够实时准确地实现基线漂移的去除．     

某高低机蜗轮磨损寿命计算研究

针对某型火炮高低机蜗轮蜗杆因磨损产生不自锁的现状,通过分析蜗轮表面磨损形貌,采用Archard磨损理论,根据蜗轮蜗杆传动的实际情况,推导出磨损计算公式并结合有限元方法,对蜗轮的磨损寿命进行计算,为预测火炮故障和实现精确化保障打下基础.     

基于可拓方法的炮兵作战指挥训练手段运用效果评价

为评价炮兵作战指挥训练手段运用效果,在分析影响炮兵作战指挥训练手段运用效果因素的基础上,应用可拓方法建立了炮兵作战指挥训练手段运用效果多指标参数的物元可拓评估模型,以定量评估结果对炮兵作战指挥训练手段运用效果进行了评价分级,并与层次分析法和模糊综合评判法的评估结果进行了比较,结论基本一致。其评估结果可为发展信息化炮兵作战指挥训练手段提供依据。