Increasing convex ordering of queue length in bulk queues

This paper considers single-server bulk queues M^(X)/G^(Y)/1 and G^(X)/M^(Y)/1. In the former queue, service times and service capacity are dependent, while in the latter queue, inter-arriving times and arriving group size are dependent. We show that stronger dependence between those leads to shorter queue lengths in the increasing convex ordering sense.     

Maximum likelihood estimation for single server queues from waiting time data

Maximum likelihood estimators for the parameters of a GI/G/1 queue are derived based on the information on waiting times {W _t },t=1,...,n, ofn successive customers. The consistency and asymptotic normality of the estimators are established. A simulation study of the M/M/1 and M/E _k /1 queues is presented.     

Tail asymptotics for the queue length in an M/G/1 retrial queue

In this paper, we study the tail behavior of the stationary queue length of an M/G/1 retrial queue. We show that the subexponential tail of the stationary queue length of an M/G/1 retrial queue is determined by that of the corresponding M/G/1 queue, and hence the stationary queue length in an M/G/1 retrial queue is subexponential if the stationary queue length in the corresponding M/G/1 queue is subexponential. Our results for subexponential tails also apply to regularly varying tails, and we provide the regularly varying tail asymptotics for the stationary queue length of the M/G/1 retrial queue. AMS subject classifications: 60J25, 60K25     

Geo/G/1 queues with disasters and general repair times

This paper discusses discrete-time single server Geo/G/1 queues that are subject to failure due to a disaster arrival. Upon a disaster arrival, all present customers leave the system. At a failure epoch, the server is turned off and the repair period immediately begins. The repair times are commonly distributed random variables. We derive the probability generating functions of the queue length distribution and the FCFS sojourn time distribution. Finally, some numerical examples are given.     

A unified algorithm for computing the stationary queue length distributions inM(k)/G/1/N and GI/M(k)/1/N queues

An iterative algorithm is developed for computing numerically the stationary queue length distributions in M/G/1/N queues with arbitrary state-dependent arrivals, or simply M(k)/G/1/N queues. The only input requirement is the Laplace-Stieltjes transform of the service time distribution.In addition, the algorithm can also be used to obtain the stationary queue length distributions in GI/M/1/N queues with state-dependent services, orGI/M(k)/1/N, after establishing a relationship between the stationary queue length distributions inGI/M(k)/1/N and M(k)/G/1/N+1 queues.Finally, we elaborate on some of the well studied special cases, such asM/G/1/N queues,M/G/1/N queues with distinct arrival rates (which includes the machine interference problems), andGI/M/C/N queues. The discussions lead to a simplified algorithm for each of the three cases.     

Stationary remaining service time conditional on queue length

In Mandelbaum and Yechiali [The conditional residual service time in the M/G/1 queue, http://www.math.tau.ac.il/∼uriy/publications (No. 30a), 1979] and in Fakinos [The expected remaining service time in a single-server queue, Oper. Res. 30 (1982) 1014-1018] a simple formula is derived for the (stationary) expected remaining service time in a M/G/1 queue, conditional on the number of customers in the system. We give a short new proof of the formula using Rate Conservation Law, and generalize to handle higher moments.     

Estimation for incomplete manpower data

Much attention has been paid to both non-parametric and parametric estimation for survival data with right censoring, particularly in the medical literature. In manpower planning the completed length of service until leaving is of great interest, and here also the data are right censored since people are still in service when data collection ends. However, it often occurs that the data are also left truncated since people are already in service at the beginning of data collection. These people have often been neglected both in estimation of the empirical distribution function and also in fitting particular parametric distributions. However, it is important to include them so as to use all the data, particularly when data are only present for a short period. The methods developed were applied to data for the completed length of service of both skilled and unskilled workers where the data were collected over a period of years. Using modified Kaplan-Meier estimation, applied to these data sets, empirical distribution functions were obtained. A number of parametric distributions were also fitted. The goodness of fit of these distributions as predictors of leavers and stayers over a given period was then tested using a chi-squared test.     

On stationary queue length distributions for G/M/s/r queues

Consider aG/M/s/r queue, where the sequence{A _n } _n=– of nonnegative interarrival times is stationary and ergodic, and the service timesS _n are i.i.d. exponentially distributed. (SinceA _n =0 is possible for somen, batch arrivals are included.) In caser < , a uniquely determined stationary process of the number of customers in the system is constructed. This extends corresponding results by Loynes [12] and Brandt [4] forr= (with=ES₀/EA₀<s) and Franken et al. [9], Borovkov [2] forr=0 ors=. Furthermore, we give a proof of the relation min(i, s)¯p(i)=p(i–1), 1ir + s, between the time- and arrival-stationary probabilities¯p(i) andp(i), respectively. This extends earlier results of Franken [7], Franken et al. [9].     

Queue length and waiting time of the M/G/1 queue under the D-policy and multiple vacations

We study the steady-state queue length and waiting time of the M/G/1 queue under the D-policy and multiple server vacations. We derive the queue length PGF and the LSTs of the workload and waiting time. Then, the mean performance measures are derived. Finally, a numerical example is presented and the effects of employing the D-policy are discussed. AMS Subject Classifications 60K25 This work was supported by the SRC/ERC program of MOST/KOSEF grant # R11-2000-073-00000.     

A GI/Geo/1 queue with negative and positive customers

The arrival of a negative customer to a queueing system causes one positive customer to be removed if any is present. Continuous-time queues with negative and positive customers have been thoroughly investigated over the last two decades. On the other hand, a discrete-time Geo/Geo/1 queue with negative and positive customers appeared only recently in the literature. We extend this Geo/Geo/1 queue to a corresponding GI/Geo/1 queue. We present both the stationary queue length distribution and the sojourn time distribution.     

Bayesian inference in Markovian queues

This paper is concerned with the Bayesian analysis of general queues with Poisson input and exponential service times. Joint posterior distribution of the arrival rate and the individual service rate is obtained from a sample consisting inn observations of the interarrival process andm complete service times. Posterior distribution of traffic intensity inM/M/c is also obtained and the statistical analysis of the ergodic condition from a decision point of view is discussed.     

Effect of stop line detection in queue length estimation at traffic signals from probe vehicles data

Stop line detectors are one of the most deployed traffic data collection technologies at signalized intersections today. Newly emerging probe vehicles are increasingly receiving more attention as an alternative means of real-time monitoring for better system operations, however, high market penetration levels are not expected in the near future. This paper focuses on real-time estimation of queue lengths by combining these two data types, i.e., actuation from stop line detectors with location and time information from probe vehicles, at isolated and undersaturated intersections. Using basic principles of statistical point estimation, analytical models are developed for the expected total queue length and its variance at the end of red interval. The study addresses the evaluation of such estimators as a function of the market penetration of probe vehicles. Accuracy of the developed models is compared using a microscopic simulation environment-VISSIM. Various numerical examples are presented to show how estimation errors behave by the inclusion of stop line detection for different volume to capacity ratio and market penetration levels. Results indicate that the addition of stop line detection improves the estimation accuracy as much as 14% when overflow queue is ignored and 24% when overflow queue is included for less than 5% probe penetration level.     

半序约束下多维正态总体均值和协方差阵的最大似然估计

对给定K个P维正态总体,未知均值和协方差阵分别为θi和Λi,i=1,2,…,k,本文考虑均值和协方差阵之间都在一个简单半序约束θ1≤θ2≤…≤θk,Λ1≥Λ2≥…≥Λk>0条件下的估计问题.讨论θi和Λi的最大似然估计的性质,并给出一个求解的迭代方法.     

具部分缺失数据的两个柏松总体的估计和检验

本文讨论部分缺失数据两柏松分布总体的参数估计和总体相同的似然比检验,证明了估计的强相合性和渐近正态性,给出了似然比检验的极限分布,并讨论了基于精确分布的检验问题.     

On normal approximation for maximum likelihood estimation from single server queues

This paper is concerned with the rate of convergence of the distribution of the maximum likelihood estimators of the arrival and the service rates in a GI/G/1 queueing system. This revised version was published online in June 2006 with corrections to the Cover Date.     

序约束下正态总体均值和方差极大似然估计的数值解法

本文讨论了k个独立正态总体的均值和方差同时在简单半序约束下的极大似然估计的求解问题,给出了计算极大估计的迭代算法,且证明该算法收敛。     

An M/G/1-type queuing model with service times depending on queue length

A study is made of an M/G/1-type queuing model in which customers receive one type of service until such time as, at the end of a service, the queue size is found to exceed a given value N, N ≥ 1. Then a second type of service is put into effect and remains in use until the queue size is reduced to a fixed value K, 0 ≤ K ≤ N. Equations are derived for the stationary probabilities both at departure times and at general times. An algorithm is developed that allows the rapid computation of the mean queue length and some important probabilities.     

Estimation for a class of generalized state-space time series models

State-space models with exponential and conjugate exponential family densities are introduced. Examples include Poisson–Gamma, Binomial–Beta, Gamma–Gamma and Normal–Normal processes. Maximum likelihood and quasilikelihood estimators and their properties are discussed. Results from a simulation study for the Poisson–Gamma model are reported.     

A Markov-modulated M/G/1 queue II: Busy period and time for buffer overflow

We consider an M/G/1 queue where the arrival and service processes are modulated by a two state Markov chain. We assume that the arrival rate, service time density and the rates at which the Markov chain switches its state, are functions of the total unfinished work (buffer content) in the queue. We compute asymptotic approximations to performance measures such as the mean residual busy period, mean length of a busy period, and the mean time to reach capacity.This research was supported in part by NSF Grants DMS-84-06110, DMS-85-01535 and DMS-86-20267, and grants from the U.S. Israel Binational Science Foundation and the Israel Academy of Sciences.     

Estimation of a common parameter for pooled samples from the uniform distributions

Summary The problem to estimate a common parameter for the pooled sample from the uniform distributions is discussed in the presence of nuisance parameters. The maximum likelihood estimator (MLE) and others are compared and it is shown that the MLE based on the pooled sample is not (asymptotically) efficient.