服务台可修的PH／PH（PH／PH）／1排队系统

本文利用准生灭过程理论系统地研究了服务台可修的ＰＨ／ＰＨ（ＰＨ／ＰＨ）／１排队系统的随机结构和性态。首先证明了在平稳状态下可修排除系统ＰＨ／ＰＨ（ＰＨ／ＰＨ）／１从排除论的角度可转化为一个等价的通常排队模型ＰＨ／ＳＭ／１，然后给出了服务台的所有可靠性指标。     

服务台可修的GI／M（M／PH）／1排队系统

本文首次讨论一个到达间隔为一般分布的可修排队系统。假定服务时间、忙期服务台寿命都服从指疏分布，修复时间是ＰＨ变量。首先证明该系统可转化为一个经典的ＧＩ／￣ＰＨ／１排队模型，然后给出系统在稳态下的各种排队论指标和可靠性指标。     

服务台可修的Geometric/G/1离散时间排队

本文讨论服务台可修的离散时间Geometric／G/1排队，平行于连续时间可修M／G／1模型，给出了系统的各种稳态指标．     

具有多重延误休假的可修排队系统M~x／G（M／G）／1（M／G）分析

具有多重延误休假的可修排队系统Ｍ~ｘ／Ｇ（Ｍ／Ｇ）／１（Ｍ／Ｇ）分析史定华（上海科技大学数学系，上海２０１８００）张文国（石家庄铁道学院基础部，石家在０５００４３）ＡＮＡＬＹＳＩＳＯＦＴＨＥＲＥＰＡＩＲＡＢＬＥＱＵＥＵＥＩＮＧＳＹＳＴＥＭＭ~ｘ／Ｇ（Ｍ...     

具有位相型修理的离散时间可修排队系统

本文研究了具有一般独立输入，位相型修理的离散时间可修排队系统，假定服务台对顾客的服务时间和服务台寿命服从几何分布，运用矩阵解析方法我们给出系统嵌入在到达时刻的稳态队长分布和等待时间分布，并证明这些分布均为离散位相型分布．我们也得到在广义服务时间内服务台发生故障次数的分布，证明它服从一个修正的几何分布．我们对离散时间可修排队与连续时间可修排队进行了比较，说明这两种排队系统在一些性能指标方面的区别之处．最后我们通过一些数值例子说明在这类系统中顾客的到达过程、服务时间和服务台的故障率之间的关系．     

多服务台可修排队的稳态分布存在条件

本文分析多服务台可修排队系统的稳态分布存在条件。多服务台可修排队系统可利用拟生灭过程理论处理。拟生灭过程方法给出了矩阵形式的多服务台可修排队系统的稳态分布存在条件。本文由这一矩阵形式的稳态分布存在条件导出具有明显概率意义的稳态分布存在条件的另一种形式，从而证明了两种不同形式的稳态分布存在条件的一致性。     

M/G1/1型可修排队的强度守恒律分析

用从平稳点过程和Palm分布理论推得的强度守恒律尝试研究了寿命为一般分布的M／G1／1型可修排队系统,在求得模型稳态工作量和拟虚等待时间表达式的基础上,得到了服务台的首次故障前时间,系统可用度,平均失效概率,服务台平均失效次数和系统故障频度等．有趣的是,当寿命分布取其特例指数分布时,与文选中已知的结果完全一致．     

离散时间服务台可修的排队系统MAP／PH（PH／PH）／1

本文研究离散时间可修排队系统,其中顾客的输入过程为离散马尔可夫到达过程（MAP）,服务台的寿命,服务台的顾客的服务时间和修理时间均为离散位相型（PH）变量,首先我们考虑广义服务过程,证明它是离散MAP,然后运用阵阵几何解理论,我们给出了系统的稳态队长分布和稳态等待时间分布,同时给出了系统的稳态可用度这一可靠性指标。     

L^2-策略休假下可修的M_1+M_2/G^x(M/G)/1匹配排队系统分析

双输人匹配排队系统是通常排队系统的一种推广．本文对该系统考察了Ｌ２－策略休假和服务台可修的两个重要因素．其中假定系统有两个不同的Ｐｏｉｓｓｏｎ输入，两类顾客按１：１作成一批进行服务，服务台的寿命服从指数分布，服务时间，修理时间和休假时间都服从一般连续型分布，利用向量马氏过程方法，得到了该排队系统的一些重要的稳态排队论指标和可靠性指标．     

可修排队系统GI/PH(M/PH)/1

在通常的排队系统中,考虑服务台在服务过程中可能失效和可修理,称之为可修排队系统(RQS).对此类排队系统的研究,继[1]之后,有[4]～[7]等.本文研究更一般的可修排队系统 GI/PH(M/PH)/1     

服务台可修的GI/PH/1排队系统

本文讨论服务台可修的GI/PH/1排队,其中服务台寿命和修复时间也是PH变量。首先证明系统在稳态下可转化为一个等价的经典GI/PH/1模型,然后给出系统的各种稳态指标。此外,对修复后重新服务和累积服务两种不同模型,我们给出了统一的处理。     

TheM/G/1 queue with processor sharing and its relation to a feedback queue

The central model of this paper is anM/M/1 queue with a general probabilistic feedback mechanism. When a customer completes his ith service, he departs from the system with probability 1–p(i) and he cycles back with probabilityp(i). The mean service time of each customer is the same for each cycle. We determine the joint distribution of the successive sojourn times of a tagged customer at his loops through the system. Subsequently we let the mean service time at each loop shrink to zero and the feedback probabilities approach one in such a way that the mean total required service time remains constant. The behaviour of the feedback queue then approaches that of anM/G/1 processor sharing queue, different choices of the feedback probabilities leading to different service time distributions in the processor sharing model. This is exploited to analyse the sojourn time distribution in theM/G/1 queue with processor sharing.Some variants are also considered, viz., anM/M/1 feedback queue with additional customers who are always present, and anM/G/1 processor sharing queue with feedback.     

A BMAP/SM/1 queue with service times depending on the arrival process

We study a BMAP/>SM/1 queue with batch Markov arrival process input and semi‐Markov service. Service times may depend on arrival phase states, that is, there are many types of arrivals which have different service time distributions. The service process is a heterogeneous Markov renewal process, and so our model necessarily includes known models. At first, we consider the first passage time from level {κ+1} (the set of the states that the number of customers in the system is κ+1) to level {κ} when a batch arrival occurs at time 0 and then a customer service included in that batch simultaneously starts. The service descipline is considered as a LIFO (Last‐In First‐Out) with preemption. This discipline has the fundamental role for the analysis of the first passage time. Using this first passage time distribution, the busy period length distribution can be obtained. The busy period remains unaltered in any service disciplines if they are work‐conserving. Next, we analyze the stationary workload distribution (the stationary virtual waiting time distribution). The workload as well as the busy period remain unaltered in any service disciplines if they are work‐conserving. Based on this fact, we derive the Laplace–Stieltjes transform for the stationary distribution of the actual waiting time under a FIFO discipline. In addition, we refer to the Laplace–Stieltjes transforms for the distributions of the actual waiting times of the individual types of customers. Using the relationship between the stationary waiting time distribution and the stationary distribution of the number of customers in the system at departure epochs, we derive the generating function for the stationary joint distribution of the numbers of different types of customers at departures. This revised version was published online in June 2006 with corrections to the Cover Date.     

带有负顾客且具有Bernoulli反馈的M/M/1工作休假排队

本文研究带反馈的具有正、负两类顾客的M/M/1工作休假排队模型.工作休假策略为空竭服务多重工作休假.负顾客一对一抵消队尾的正顾客(若有),若系统中无正顾客时,到达的负顾客自动消失,负顾客不接受服务.完成服务的正顾客以概率p(0相似文献   

批到达M/G/1重试排队的队长的尾渐近

用随机分解法研究成批到达服务时间为次指数分布的重试排队中队长的尾行为,得到了该系统与其相应的标准排队系统队长尾分布的关系;对次指数尾,结果也能用于正则变化尾,进而得到正则变化尾渐近．     

Stationary tail asymptotics of a tandem queue with feedback

Motivated by applications in manufacturing systems and computer networks, in this paper, we consider a tandem queue with feedback. In this model, the i.i.d. interarrival times and the i.i.d. service times are both exponential and independent. Upon completion of a service at the second station, the customer either leaves the system with probability p or goes back, together with all customers currently waiting in the second queue, to the first queue with probability 1−p. For any fixed number of customers in one queue (either queue 1 or queue 2), using newly developed methods we study properties of the exactly geometric tail asymptotics as the number of customers in the other queue increases to infinity. We hope that this work can serve as a demonstration of how to deal with a block generating function of GI/M/1 type, and an illustration of how the boundary behaviour can affect the tail decay rate.     

Bayesian prediction inM/M/1 queues

Simple queues with Poisson input and exponential service times are considered to illustrate how well-suited Bayesian methods are used to handle the common inferential aims that appear when dealing with queue problems. The emphasis will mainly be placed on prediction; in particular, we study the predictive distribution of usual measures of effectiveness in anM/M/1 queue system, such as the number of customers in the queue and in the system, the waiting time in the queue and in the system, the length of an idle period and the length of a busy period.     

Controlling the GI/M/1 queue by conditional acceptance of customers

In this paper we consider the problem of controlling the arrival of customers into a GI/M/1 service station. It is known that when the decisions controlling the system are made only at arrival epochs, the optimal acceptance strategy is of a control-limit type, i.e., an arrival is accepted if and only if fewer than n customers are present in the system. The question is whether exercising conditional acceptance can further increase the expected long run average profit of a firm which operates the system. To reveal the relevance of conditional acceptance we consider an extension of the control-limit rule in which the nth customer is conditionally admitted to the queue. This customer may later be rejected if neither service completion nor arrival has occurred within a given time period since the last arrival epoch. We model the system as a semi-Markov decision process, and develop conditions under which such a policy is preferable to the simple control-limit rule.     

一类多站循环服务系统的状态与状态转移

探讨具有如下特征的多站循环服务系统：（１）队列容量有限;（２）每次服务对象受限;（３）实施非门限方式。论述的主要内容有：系统与队列运行特点;队列在服务期间的状态转移;队列在周期中的状态与状态转移;系统与队列的有关参量近似求解。     

带RCE抵消策略的负顾客M/M/1工作休假排队系统

考虑服务员在休假期间不是完全停止工作,而是以相对于正常工作时低些的速率服务顾客的M/M/1工作休假排队模型.在此模型基础上,笔者针对现实的M/M/1排队模型中可能出现的外来干扰因素,提出了带RCE(Removal of Customers at the End)抵消策略的负顾客M/M/1工作休假排队这一新的模型.服务规则为先到先服务.工作休假策略为空竭服务多重工作休假.抵消原则为负顾客一对一抵消队尾的正顾客,若系统中无正顾客时,到达的负顾客自动消失,负顾客不接受服务.使用拟生灭过程和矩阵几何解方法给出了系统队长的稳态分布,证明了系统队长和等待时间的随机分解结果并给出稳态下系统中正顾客的平均队长和顾客在系统中的平均等待时间.