M/G/1排队系统的性能灵敏度分析

非Markov型排除系统经常被用来作为某些实际工程问题（如通讯网络）的研究模型,对于一般的M／G／1排队系统,本文通过研究其嵌入Markov链,讨论了系统的稳态性能灵敏度分析问题,并给出用嵌入Markov链的势能表示的稳态性能灵敏度公式,由于嵌入Markov链要比描述其系统状态的半Markov过程简单得多,故本文的结果对M／G／1排队系统的性能灵敏度仿真计算及系统的优化,都将带来极大的方便。     

GI／PH／1休假排队系统队长的随机分解

对空竭服务、多重休假规则的GI/PH/1排队系统的稳态行为给出了详尽分析。在休假时间服从负指数分布情况下,讨论了到达点嵌入Markov链的结构、平衡条件和稳态队长。证明稳态队长可分解成两个独立随机变量之和。     

一类批量服务排队系统的求解

给出一类特殊的批量服务排队系统-公交系统的稳态概率分布的求解过程，并在此基础上给出这类服务系统平均队长的算法，中给出具体例子说明计算过程。     

带关闭期和启动期的GI/M/1排队及其应用

本研究了带关闭期和启动期的GI/M/1排队，给出了稳态队长分布和等待时间分布的随机分解，展示了它在计算机通讯网络中的应用。     

带有启动时间单重休假的Geom/G/1排队

本研究带有启动时间的单重休假Geom/G/1离散时间排队，导出了稳态队长、等待时间的分布和母函数及其随机分解结果和稳态系统忙期的分析。     

启动延迟N-策略批到达多重休假排队

目前N-策略批到达排队系统稳态队长分布难以给出解析解.提出一种新的递归算法研究顾客批到达,服务台延迟启动且多重休假的N-策略休假排队系统稳态队长分布.首先采用条件随机分解的方法得到稳态队长分布的概率母函数;然后采用递归算法推导附加队长分布的解析表达式;最后推导出稳态队长分布的递推关系式.     

离散时间排队MAP/PH/3

本文研究具有马尔可夫到达过程的离散时间排队MAP/PH/3,系统中有三个服务台,每个服务台对顾客的服务时间均服从位相型分布。运用矩阵几何解的理论,我们给出了系统平稳的充要条件和系统的稳态队长分布。同时我们也给出了到达顾客所见队长分布和平均等待时间。     

M/G/1工作休假和休假中止排队

本文分析了一个泊松到达、一般服务的单服务台休假排队，休假策略是工作休假和休假中止．通过嵌入马氏链的方法给出了系统稳态条件，并通过补充变量的方法给出了系统稳态队长的概率母函数。关键词：M／G／1排队系统；工作休假和休假中止；嵌入马氏链；补充变量法     

截超泊松排队：具有阻碍,放弃和不同服务员HK／M／2N系统

本文讨论具有阻碍、放弃,不同服务员ＫＫ／Ｍ／２／Ｎ排队系统的解析解。对经典的一种先入先出的修改排队规则在较一般的条件下被采用了,得到了稳态概率和一些有效度量的显式。一些特殊情况也被化简了。     

部分服务台同步多重体假的M／Mc排队

本文研究只允许部分服务台休假的M／M／c排队系统,讨论了两类不同的同步多重休假模型,给出了稳态指标的计算方法和条件随机分解结果。     

A new method of performance sensitivity analysis for non-Markovian queueing networks

The paper develops a new method of calculating and estimating the sensitivities of a class of performance measures with respect to a parameter of the service or interarrival time distributions in queueing networks. The distribution functions may be of a general form. The study is based on perturbation analysis of queueing networks. A new concept, the realization factor of a perturbation, is introduced for the network studied. The properties of realization factors are discussed, and a set of linear differential equations specifying the realization factors are derived. The sensitivity of the steady-state performance with respect to a parameter can be expressed in a simple form using realization factors. Based on this, the sensitivity can be estimated by applying a perturbation analysis algorithm to a sample path of the system. We show that the derivative of the performance measure with respect to a parameter based on a single sample path converges with probability one to the derivative of the steady-state performance as the length of the sample path goes to infinity. The results provide a new analytical method of calculating performance sensitivities and justifies the application of perturbation analysis algorithms to non-Markovian queueing networks.     

Optimal Server Acquisition in Open Queueing Networks

Several production and flexible manufacturing systems can naturally be modelled using queueing networks. In this paper, we consider the problem of acquiring servers for the nodes of an open queueing network, so as to optimize the steady-state mean virtual system parameters subject to a budget constraint. A partial enumeration scheme and a heuristic method have been proposed to solve this problem. Empirical results based on randomly generated test problems are used to identify a class of problems for which the heuristic performs well.     

Simulation methods for queues: An overview

This paper gives an overview of those aspects of simulation methodology that are (to some extent) peculiar to the simulation of queueing systems. A generalized semi-Markov process framework for describing queueing systems is used through much of the paper. The main topics covered are: output analysis for simulation of transient and steady-state quantities, variance reduction methods that exploit queueing structure, and gradient estimation methods for performance parameters associated with queueing networks.The research of this author was supported by the U.S. Army Research Office under Contract DAAG29-84-K-0030.The research of this author was supported by the U.S. Army Research Office under Contract DAAG29-84-K-0030 and National Science Foundation Grant DCR-85-09668.     

����˿͹����Ŷ�ϵͳ����Ϣ����

The discriminatory processor sharing queues with multiple classes of customers (abbreviated as DPS queues) are an important but difficult research direction in queueing theory, and it has many important practical applications in the fields of, such as, computer networks, manufacturing systems, transportation networks, and so forth. Recently, researchers have carried out some key work for the DPS queues. They gave the generating function of the steady-state joint queue lengths, which leads to the first two moments of the steady-state joint queue lengths. However, using the generating function to provide explicit expressions for the steady-state joint queue lengths has been a difficult and challenging problem for many years. Based on this, this paper applies the maximum entropy principle in the information theory to providing an approximate expression with high precision, and this approximate expression can have the same first three moments as those of its exact expression. On the other hand, this paper gives efficiently numerical computation by means of this approximate expression, and analyzes how the key variables of this approximate expression depend on the original parameters of this queueing system in terms of some numerical experiments. Therefore, this approximate expression has important theoretical significance to promote practical applications of the DPS queues. At the same time, not only do the methodology and results given in this paper provide a new line in the study of DPS queues, but they also provide the theoretical basis and technical support for how to apply the information theory to the study of queueing systems, queueing networks and more generally, stochastic models.     

The achievable region method in the optimal control of queueing systems; formulations,bounds and policies

We survey a new approach that the author and his co-workers have developed to formulate stochastic control problems (predominantly queueing systems) asmathematical programming problems. The central idea is to characterize the region of achievable performance in a stochastic control problem, i.e., find linear or nonlinear constraints on the performance vectors that all policies satisfy. We present linear and nonlinear relaxations of the performance space for the following problems: Indexable systems (multiclass single station queues and multiarmed bandit problems), restless bandit problems, polling systems, multiclass queueing and loss networks. These relaxations lead to bounds on the performance of an optimal policy. Using information from the relaxations we construct heuristic nearly optimal policies. The theme in the paper is the thesis that better formulations lead to deeper understanding and better solution methods. Overall the proposed approach for stochastic control problems parallels efforts of the mathematical programming community in the last twenty years to develop sharper formulations (polyhedral combinatorics and more recently nonlinear relaxations) and leads to new insights ranging from a complete characterization and new algorithms for indexable systems to tight lower bounds and nearly optimal algorithms for restless bandit problems, polling systems, multiclass queueing and loss networks.     

A General Decomposition Algorithm for Parallel Queues with Correlated Arrivals

Queueing with correlated arrivals occurs when customers arrive at a set of queues simultaneously. The difficulty in analyzing systems with correlated arrivals is due to the fact that the individual queueing systems are stochastically dependent. Exact methods for analyzing these systems are computationally intensive and are limited to only a few special cases. In this paper, we consider a system of parallel queues with bulk service and correlated arrivals. We show how the matrix-geometric approach can be used to obtain the performance measures of the system. We also develop an algorithm for large systems that efficiently approximates the performance measures by decomposing it into individual queueing systems. Finally, we describe how the principles of our decomposition algorithm can be extended to analyze a variety of different parallel queueing systems with correlated arrivals. We then evaluate the accuracy of our algorithm through a numerical study.     

Performance optimization of queueing systems with perturbation realization

After the intensive studies of queueing theory in the past decades, many excellent results in performance analysis have been obtained, and successful examples abound. However, exploring special features of queueing systems directly in performance optimization still seems to be a territory not very well cultivated. Recent progresses of perturbation analysis (PA) and sensitivity-based optimization provide a new perspective of performance optimization of queueing systems. PA utilizes the structural information of queueing systems to efficiently extract the performance sensitivity information from a sample path of system. This paper gives a brief review of PA and performance optimization of queueing systems, focusing on a fundamental concept called perturbation realization factors, which captures the special dynamic feature of a queueing system. With the perturbation realization factors as building blocks, the performance derivative formula and performance difference formula can be obtained. With performance derivatives, gradient-based optimization can be derived, while with performance difference, policy iteration and optimality equations can be derived. These two fundamental formulas provide a foundation for performance optimization of queueing systems from a sensitivity-based point of view. We hope this survey may provide some inspirations on this promising research topic.     

On the poisson output of queueing systems with dependent service times

In this paper a method is stated to conclude that the output of given queueing system is POISSON from the steady-state probabilities and from the behavior of the queueing system at jump epochs, i.e. at epochs when the system state can be changed. The corresponding statement for queueing systems described by Markov processes with denumber-able state space will be generalized to systems which can have arbitrary service time distributions if the steady-state probabilities are insensitive with respect to these distributions.