离散时间优先队列的尾部渐近性分析（英文）

本文研究在离散情形下,两类不同优先权的顾客进入服务系统的情况.稳态概率可以用矩阵形式表示出来.用矩阵分析法,联合稳态概率在一定条件下几何衰减.     

具有两阶段服务和服务台故障M/M/1/N多重休假排队系统

研究了具有两阶段服务和服务台故障的M/M/1/N多重休假排队系统.利用马尔可夫过程理论建立了系统稳态概率方程组,并利用分块矩阵解法,得到了稳态概率的矩阵解.然后由此得出了系统的平均队长、平均等待队长等性能指标.     

单重工作休假M/M/c排队驱动的流体模型分析

该文在M/M/c排队驱动系统中加入工作休假策略,研究了单重工作休假多服务台排队驱动的流体模型.利用拟生灭过程和矩阵几何解法得到驱动系统稳态队长分布.构建净输入率结构,导出流体模型的稳态联合分布函数满足的的矩阵微分方程组,进而利用Laplace-Stieltjes变换(LST)方法得到稳态下缓冲器库存量的空库概率及均值表...     

带启动-关闭期和N策略的多重休假M/G/1排队

研究多重休假带启动-关闭期和N策略的M/G/1排队系统,根据嵌入Markov链的方法推导出状态转移概率矩阵,利用M/G/1型排队系统结构矩阵解析法,得出顾客服务完离去后系统稳态队长分布及其母函数的表达式;从而由经典随机分解原理,给出稳态队长的随机分解结果.此外,利用LST变换处理卷积,得到忙期的母函数及数学期望的表达式;进而得到忙期、启动期和关闭期的母函数及在稳态下服务员处于各状态的概率.最后提出一些数值例子以验证结论.     

多服务台服务同一顾客的M/M/m+k/N可修排队系统

研究带有备用服务台的可修排队系统,假设多个服务台可同时服务同一顾客,利用马尔可夫过程理论建立了系统稳态方程组,然后利用分块矩阵的解法求出系统稳态概率的矩阵解,在此基础上建立系统的费用模型,并利用Matlab软件进行数值实例分析.     

带有止步和状态相依的M/Ej/1/N排队系统的矩阵解法

研究了带有止步和服务率依赖于状态的M/Ej/1/N排队系统.顾客到达系统时,以一定的概率选择进人系统或止步(不进人系统).顾客接受服务的服务率依赖于系统中的顾客数,当系统中的顾客数不超过临界值k时,服务员慢速服务;否则,服务员快速服务.利用分块矩阵的方法,推出了稳态概率向量所满足的矩阵形式的迭代公式,给出了稳态概率的表达式和计算过程.作为特例,考虑了N=4时系统稳态概率的计算.在此基础上,还求出了系统的一些性能指标,并建立了以临界值k为控制变量的费用模型.通过数值分析,求出了使费用函数最小的最优临界值k*,并进一步研究了模型参数对最优临界值和最优费用的影响.     

带有止步和状态相依的M/Ej/1/N排队系统的矩阵解法

研究了带有止步和服务率依赖于状态的M/Ej/1/N排队系统.顾客到达系统时,以一定的概率选择进入系统或止步(不进入系统).顾客接受服务的服务率依赖于系统中的顾客数,当系统中的顾客数不超过临界值k时,服务员慢速服务;否则,服务员快速服务.利用分块矩阵的方法,推出了稳态概率向量所满足的矩阵形式的迭代公式,给出了稳态概率的表达式和计算过程.作为特例,考虑了N=4时系统稳态概率的计算.在此基础上,还求出了系统的一些性能指标,并建立了以临界值k为控制变量的费用模型.通过数值分析,求出了使费用函数最小的最优临界值k*,并进一步研究了模型参数对最优临界值和最优费用的影响.     

多重工作休假的Geom/Geom/(Geom/Geom)/H双输入排队系统

本文研究多重工作休假的Geom/Geom/(Geom/Geom)/H双输入排队的问题.利用Markov链及矩阵几何解的方法,获得所研究的模型,建立稳态概率满足的方程组,进而推导出稳态队长分布、服务台消失的概率,推广了排队系统的模型及相关的结果.     

具有工作故障及有限容量的MAP/M/1排队系统性能分析

为了拓展随机排队理论,在具有工作故障的MAP/M/1排队的基础上,引入有限容量策略建立起一个新的排队模型.通过Uniformization Technique将连续时间排队模型转化成对应的离散时间排队模型,运用矩阵几何组合解给出系统中的顾客数量和服务器状态的联合稳态概率表达式,并给出基于稳态概率的性能指标.最后通过一些数值例子展示参数对性能指标的影响.     

带止步与中途退出策略的M~x/M/1/N单重工作休假排队系统

研究了带有止步和中途退出的M~x/M/1/N单重工作休假排队系统.顾客成批到达,到达后每批中的顾客,或者以概率b决定进入队列等待服务,或者以概率1-b止步(不进入系统).顾客进入系统后可能因为等待的不耐烦而在没有接受服务的情况下离开系统(中途退出).系统中一旦没有顾客,服务员立即进入单重工作休假.首先,利用马尔科夫过程理论建立了系统稳态概率满足的方程组.其次利用矩阵解法求出了稳态概率的矩阵解并得到了系统的平均队长、平均等待队长以及顾客的平均消失概率等性能指标.最后通过数值例子分析了工作休假时的低服务率η和休假率θ这两个参数对系统平均队长的影响.     

Spanning Forests of Digraphs and Limiting Probabilities of Markov Chains

A maximum out forest of a digraph is its spanning subgraph that consists of disjoint diverging trees and has the maximum possible number of arcs. For an arbitrary weighted digraph, we consider a matrix of specific weights of maximum out forests and demonstrate how this matrix can be used to get a graph-theoretic interpretation for the limiting probabilities of Markov chains. For a special (nonclassical) correspondence between Markov chains and weighted digraphs, the matrix of Cesáro limiting transition probabilities of any finite homogeneous Markov chain coincides with the normalized matrix of maximum out forests of the corresponding digraphs. This provides a finite (combinatorial) method to calculate the limiting probabilities of Markov chains and thus their stationary distributions. On the other hand, the Markov chain technique provides the proofs to some statements about digraphs.     

The effect of punishment duration of trigger strategies and quasifinite continuation probabilities for Prisoners' Dilemmas

Limiting inspection to publicly correlated strategies linearizes the problem of finding subgame perfect equilibria for indefinitely repeated Prisoners' Dilemmas. Equilibrium strategies satisfy a matrix inequality; the matrix depends on the duration of the punishment mechanism. The existence of subgame perfect equilibria is determined by comparing a parameter of the stage game to the spectral radius of the matrix. The spectral radii are found for the matrices associated with every possible duration of punishment.  Quasifinite continuation probabilities are defined to be the set of continuation probabilities where the sole subgame perfect equilibrium is noncooperative for any Prisoners' Dilemma stage game. The defining property of quasifinite continuation probabilities is determined by a common factor of the different spectral radii. Additional properties of quasifinite continuation probabilities are examined. Received: January 1996/final version: January 1999     

Computing absorption probabilities for a Markov chain

We present a new matrix construction algorithm for computing absorption probabilities for a finite, reducible Markov chain. The construction algorithm contains two steps: matrix augmentation and matrix reduction. The algorithm requires more memory and less execution time than the calculation of absorption probabilities by the LU decomposition. We apply the algorithm to a Markovian model of a production line.     

Probabilities of Pure Nash Equilibria in Matrix Games when the Payoff Entries of One Player Are Randomly Selected

The Nash equilibrium in pure strategies represents an important solution concept in nonzero sum matrix games. Existence of Nash equilibria in games with known and with randomly selected payoff entries have been studied extensively. In many real games, however, a player may know his own payoff entries but not the payoff entries of the other player. In this paper, we consider nonzero sum matrix games where the payoff entries of one player are known, but the payoff entries of the other player are assumed to be randomly selected. We are interested in determining the probabilities of existence of pure Nash equilibria in such games. We characterize these probabilities by first determining the finite space of ordinal matrix games that corresponds to the infinite space of matrix games with random entries for only one player. We then partition this space into mutually exclusive spaces that correspond to games with no Nash equilibria and with r Nash equilibria. In order to effectively compute the sizes of these spaces, we introduce the concept of top-rated preferences minimal ordinal games. We then present a theorem which provides a mechanism for computing the number of games in each of these mutually exclusive spaces, which then can be used to determine the probabilities. Finally, we summarize the results by deriving the probabilities of existence of unique, nonunique, and no Nash equilibria, and we present an illustrative example.     

Linear independence of root equations forM/G/1 type Markov chains

There is a classical technique for determining the equilibrium probabilities ofM/G/1 type Markov chains. After transforming the equilibrium balance equations of the chain, one obtains an equivalent system of equations in analytic functions to be solved. This method requires finding all singularities of a given matrix function in the unit disk and then using them to obtain a set of linear equations in the finite number of unknown boundary probabilities. The remaining probabilities and other measures of interest are then computed from the boundary probabilities. Under certain technical assumptions, the linear independence of the resulting equations is established by a direct argument involving only elementary results from matrix theory and complex analysis. Simple conditions for the ergodicity and nonergodicity of the chain are also given.     

Perturbed Markov Chains with Damping Component

The paper is devoted to studies of regularly and singularly perturbed Markov chains with damping component. In such models, a matrix of transition probabilities is regularised by adding a special damping matrix multiplied by a small damping (perturbation) parameter ε. We perform a detailed perturbation analysis for such Markov chains, particularly, give effective upper bounds for the rate of approximation for stationary distributions of unperturbed Markov chains by stationary distributions of perturbed Markov chains with regularised matrices of transition probabilities, asymptotic expansions for approximating stationary distributions with respect to damping parameter, explicit coupling type upper bounds for the rate of convergence in ergodic theorems for n-step transition probabilities, as well as ergodic theorems in triangular array mode.

     

Note on “Obtaining the Maximum Likelihood Estimates in Incomplete R × C Contingency Tables Using a Poisson Generalized Linear Model”

Abstract

This note extends the construction of the design matrix used for estimating cell probabilities with ignorable missing data described by Lipsitz, Parzen, and Molenberghs. A reformulation for the general case of an n-way table is described and implemented in a SAS macro program. The macro constructs this design matrix and offset variable, estimates the cell probabilities, and returns a table with the estimates, their standard errors, and fitted cell frequencies.     

Ruin Probability in a Semi-Markov Risk Model with Constant Interest Force and Heavy-Tailed Claims

In the present paper, we consider a kind of semi-Markov risk model (SMRM) with constant interest force and heavy-tailed claims, in which the claim rates and sizes are conditionally independent, both fluctuating according to the state of the risk business. First, we derive a matrix integro-differential equation satisfied by the survival probabilities. Second, we analyze the asymptotic behaviors of ruin probabilities in a two-state SMRM with special claim amounts. It is shown that the asymptotic behaviors of ruin probabilities depend only on the state 2 with heavy-tailed claim amounts, not on the state 1 with exponential claim sizes.     

用改进遗传算法求解矩阵实特征值

依据矩阵特征值的分布理论,通过确定矩阵实特征值的分布区域,用实数编码和具有自适应交叉概率和变异概率的遗传算法来求解矩阵实特征值的近似值.仿真结果表明,此算法可以达到一定的精度,具有一定的通用性.并给求矩阵特征值提供了一种快速的方法.