Queueing Models for Out-Patient Appointment Systems — a Case Study

Some recent research on queueing models is successfully applied to the problem of designing an appropriate appointment system for the out-patient department at the Royal Lancaster Infirmary. Although it is acknowledged that improving appointment systems is not simply a modelling problem, it is nevertheless argued that the model used here could be an effective tool in local studies.     

A queueing network analysis of a health center

This paper shows how a queueing network model helped to uncover the causes of delay in a health center appointment clinic. Patients, clerks, technicians, doctors and nurses agreed that the clerical registration area was the major bottleneck in the system. Our first reaction was to simulate the system with special attention on the complex registration procedure. Time constraints on data collection and program development led us to a queueing network model and QNA, a software tool for analyzing queueing networks developed by Whitt. The queueing analysis showed the registration area was not the bottleneck and we conjectured that delays were due to scheduling problems. A preliminary trial in the clinic of a modified appointment system showed promise with a 20 minute reduction in average time in the system (based on a small sample). Although there were significant differences between features of the real system and assumptions in the queueing network model, the queueing network model yielded insight into the operation of the appointment clinic.     

On a dual hybrid queueing system

This article deals with a hybrid system, in which a single server processes two different queues of units, one called primary and the other one — secondary. The queueing process in the primary system is formed by a Poisson flow of groups of units, while the secondary system is closed. The server’s primary appointment (in hybrid mode I) is to process units in batches until the buffer content drops significantly. In this case, the server takes over a queue in the secondary system (activating hybrid mode II), and he is to complete some minimum amount of jobs (rendered in groups of random sizes during random times). When he is done with this work, he returns to the primary system. If the queue there is not long enough, he waits, thereby activating hybrid mode III. The authors first apply and embellish some techniques from fluctuation theory to find the exit times from respective hybrid modes and queue levels in both systems in terms of their joint functionals. The results are then utilized for the subsequent (semi-regenerative) analysis of the evolution of queueing processes. The authors obtain explicit formulas for the limiting distribution of the queueing process and the mean number of units processed in the secondary system.     

Queueing models for appointment-driven systems

Many service systems are appointment-driven. In such systems, customers make an appointment and join an external queue (also referred to as the “waiting list”). At the appointed date, the customer arrives at the service facility, joins an internal queue and receives service during a service session. After service, the customer leaves the system. Important measures of interest include the size of the waiting list, the waiting time at the service facility and server overtime. These performance measures may support strategic decision making concerning server capacity (e.g. how often, when and for how long should a server be online). We develop a new model to assess these performance measures. The model is a combination of a vacation queueing system and an appointment system.     

Staffing a service system with appointment-based customer arrivals

Appointment systems are widely used to facilitate customers’ access to services in many industries such as healthcare. A number of studies have taken a queueing approach to analyse service systems and facilitate managerial decisions on staffing requirements by assuming independent and stationary customer arrivals. This paper is motivated by the observation that the queueing-based method shows relatively poor performance when customers arrive according to their appointment times. Because customer arrivals are dependent on their appointment times, this study, unlike queueing-based methods, conducts a detailed analysis of appointment-based customer arrivals instead of making steady-state assumptions. We develop a new model that captures the characteristics of appointment-based customer arrivals and computes the probability of transient system states. Through the use of this model, which relaxes stationary and independent assumptions, we propose a heuristic algorithm that determines staffing requirements with aims to minimizing staff-hours while satisfying a target service level. The simulation results show that the proposed method outperforms the queueing-based method.     

Analysis of a Two‐Phase Queueing System with Vacations and Bernoulli Feedback

Abstract

We consider a two‐phase queueing system with server vacations and Bernoulli feedback. Customers arrive at the system according to a Poisson process and receive batch service in the first phase followed by individual services in the second phase. Each customer who completes the individual service returns to the tail of the second phase service queue with probability 1 ? σ. If the system becomes empty at the moment of the completion of the second phase services, the server takes vacations until he finds customers. This type of queueing problem can be easily found in computer and telecommunication systems. By deriving a relationship between the generating functions for the system size at various embedded epochs, we obtain the system size distribution at an arbitrary time. The exhaustive and gated cases for the batch service are considered.     

考虑存在取消预约情形的门诊预约能力分配策略

在现实的门诊预约问题中,已经预约的患者在接收医疗服务之前,有可能取消先前的预约,这会对医院的收益造成负面影响,如何在考虑患者存在取消预约的情形下,设计合理有效的能力分配策略来保证医院的收益,是一个值得研究的问题.本文针对具有提前预约和当天预约的门诊预约能力分配问题,在考虑提前预约患者可能存在取消预约行为的情形下,提出了一种提前预约患者和当天预约患者的最优能力分配策略。文中首先以医院的期望收益最大作为决策目标,建立了存在取消预约患者的医疗预约问题的马尔科夫过程模型,并给出了该模型的相关性质;基于所建立模型的特征,证明了对于任意的提前预约时段,存在提前预约患者的最佳数量,进而给出了提前预约患者和当天预约患者的最优能力分配策略以及确定该策略的精确算法;最后,通过数值试验说明了本文所提出的能力分配策略的适用性和有效性。     

Optimal Control of an M/G/1/K Queueing System with Combined <Emphasis Type="Italic">F</Emphasis> Policy and Startup Time

We investigate the optimal management problem of an M/G/1/K queueing system with combined F policy and an exponential startup time. The F policy queueing problem investigates the most common issue of controlling the arrival to a queueing system. We present a recursive method, using the supplementary variable technique and treating the supplementary variable as the remaining service time, to obtain the steady state probability distribution of the number of customers in the system. The method is illustrated analytically for exponential service time distribution. A cost model is established to determine the optimal management F policy at minimum cost. We use an efficient Maple computer program to calculate the optimal value of F and some system performance measures. Sensitivity analysis is also investigated.     

Modeling the transplant waiting list: A queueing model with reneging

Motivated by the problem of organ allocation, we develop a queueing model with reneging that provides a stylistic representation of the transplant waiting list. The model assumes that there are several classes of patients, several classes of organs, and patient reneging due to death. We focus on randomized organ allocation policies and develop closed-form asymptotic expressions for the stationary waiting time, stationary waiting time until transplantation, and fraction of patients who receive transplantation for each patient class. Analysis of these expressions identifies the main factors that underlie the performance of the transplant waiting list and demonstrates that queueing models can prove useful when evaluating the organ allocation system. This revised version was published online in June 2006 with corrections to the Cover Date.     

Mean Response Times in Accessing a Time-Sharing Computer

In a time-sharing computer system a queueing problem arose whose solution could not be found easily using classical queueing techniques. The assumption of an exponential distribution for the time between arriving messages has enabled a theory to be constructed to find the average response times for customers. Since the system modelled is a simple interrogation service the analysis and results should be of general use. In particular the distributions of service times required by the customers can be quite general.     

Optimal buffer size and dynamic rate control for a queueing system with impatient customers in heavy traffic

We address a rate control problem associated with a single server Markovian queueing system with customer abandonment in heavy traffic. The controller can choose a buffer size for the queueing system and also can dynamically control the service rate (equivalently the arrival rate) depending on the current state of the system. An infinite horizon cost minimization problem is considered here. The cost function includes a penalty for each rejected customer, a control cost related to the adjustment of the service rate and a penalty for each abandoning customer. We obtain an explicit optimal strategy for the limiting diffusion control problem (the Brownian control problem or BCP) which consists of a threshold-type optimal rejection process and a feedback-type optimal drift control. This solution is then used to construct an asymptotically optimal control policy, i.e. an optimal buffer size and an optimal service rate for the queueing system in heavy traffic. The properties of generalized regulator maps and weak convergence techniques are employed to prove the asymptotic optimality of this policy. In addition, we identify the parameter regimes where the infinite buffer size is optimal.     

A queueing system with random server capacity and multiple control

The authors study queueing, input and output processes in a queueing system with bulk service and state dependent service delay. The input flow of customers, modulated by a semi-Markov process, is served by a single server that takes batches of a certain fixed size if available or waits until the queue accumulates enough customers for service. In the latter case, the batch taken for service is of random size dependent on the state of the system, while service duration depends both on the state of the system and on the batch size taken. The authors establish a necessary and sufficient condition for equilibrium of the system and obtain the following results: Explicit formulas for steady state distribution of the queueing process, intensity of the input and output processes, and mean values of idle and busy periods. They employ theory of semi-regenerative processes and illustrate the results by a number of examples. In one of them an optimization problem is discussed.     

B.A. Sevastyanov’s famous theorem

In 1956, at the Third All-Union Mathematical Congress, Boris Aleksandrovich Sevastyanov gave a talk on the ergodic theorem proved by him for Markov processes and on its application to queueing systems. In 1957, this result was published in the journal Teoriya Veroyatnostei i Ee Primeneniya (Theory of Probability and Its Applications). An important corollary to the ergodic theorem is a generalization of Erlang’s well-known formula to a queueing system with a Poisson input flow and an arbitrary distribution of the service time. This result of Sevastyanov has served as a starting point for numerous studies on the problem, which was later called the insensitivity (invariance) problem for queueing systems with losses. There are hundreds of references to this result of Sevastyanov.     

A disaster queue with Markovian arrivals and impatient customers

We consider a single server queueing system in which arrivals occur according to a Markovian arrival process. The system is subject to disastrous failures at which times all customers in the system are lost. Arrivals occurring during the time the system undergoes repair are stored in a buffer of finite capacity. These customers can become impatient after waiting a random amount of time and leave the system. However, these customers do not become impatient once the system becomes operable. When the system is operable, there is no limit on the number of customers who can be admitted. The structure of this queueing model is of GI/M/1-type that has been extensively studied by Neuts and others. The model is analyzed in steady state by exploiting the special nature of this type queueing model. A number of useful performance measures along with some illustrative examples are reported.     

Threshold control by a single-server retrial queue with batch arrivals and group services

A controlled single-server retrial queueing system is investigated. Customers arrive according to batch Markovian arrival process. The system has several operation modes which are controlled by means of a threshold strategy. The stationary distribution is calculated. Optimization problem is considered and a numerical example is presented.     

Scheduling networks of queues: Heavy traffic analysis of a simple open network

We consider a queueing network with two single-server stations and two types of customers. Customers of type A require service only at station 1 and customers of type B require service first at station 1 and then at station 2. Each server has a different general service time distribution, and each customer type has a different general interarrival time distribution. The problem is to find a dynamic sequencing policy at station 1 that minimizes the long-run average expected number of customers in the system.The scheduling problem is approximated by a dynamic control problem involving Brownian motion. A reformulation of this control problem is solved, and the solution is interpreted in terms of the queueing system in order to obtain an effective sequencing policy. Also, a pathwise lower bound (for any sequencing policy) is obtained for the total number of customers in the network. We show via simulation that the relative difference between the performance of the proposed policy and the pathwise lower bound becomes small as the load on the network is increased toward the heavy traffic limit.     

A recursive method for the F-policy G/M/1/K queueing system with an exponential startup time

This paper deals with the optimal control of a finite capacity G/M/1 queueing system combined the F-policy and an exponential startup time before start allowing customers in the system. The F-policy queueing problem investigates the most common issue of controlling arrival to a queueing system. We provide a recursive method, using the supplementary variable technique and treating the supplementary variable as the remaining interarrival time, to develop the steady-state probability distribution of the number of customers in the system. We illustrate a recursive method by presenting three simple examples for exponential, 3-stage Erlang, and deterministic interarrival time distributions, respectively. A cost model is developed to determine the optimal management F-policy at minimum cost. We use an efficient Maple computer program to determine the optimal operating F-policy and some system performance measures. Sensitivity analysis is also studied.     

成批到达排队系统的随机比较

本文研究成批到达排队系统中队长过程的随机比较问题．利用随机比较方法我们对成批到达指数服务的多服务台排队系统进行分析,得到了该排队系统中队长过程的随机比较以及队长函数关于时间的凹性和凸性．同时我们也给出了成批到达一般服务的单服务台排队系统队长过程、稳态队长的随机比较以及队长函数关于时间的凹性和凸性．     

An approximate analysis of a cyclic server queue with limited service and reservations

In this paper, we examine a queueing problem motivated by the pipeline polling protocol in satellite communications. The model is an extension of the cyclic queueing system withM-limited service. In this service mechanism, each queue, after receiving service on cyclej, makes a reservation for its service requirement in cyclej + 1. The main contribution to queueing theory is that we propose an approximation for the queue length and sojourn-time distributions for this discipline. Most approximate studies on cyclic queues, which have been considered before, examine the means only. Our method is an iterative one, which we prove to be convergent by using stochastic dominance arguments. We examine the performance of our algorithm by comparing it to simulations and show that the results are very good.     

带有负顾客的M/M/c多重工作休假排队

考虑服务台在休假期间不是完全停止工作,而是以相对于正常服务期低些的服务率服务顾客的M/M/c工作休假排队模型.在此模型基础上,针对现实的M/M/c排队模型中可能出现的外来干扰因素,提出了带有负顾客的M/M/c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异步多重工作休假.抵消原则为负顾客一对一抵消处于正常服务期的正顾客,若系统中无处于正常服务期的正顾客时,到达的负顾客自动消失,负顾客不接受服务.首先,由该多重休假模型得到其拟生灭过程及生成元矩阵,然后运用矩阵几何方法给出系统队长的稳态分布表达式和若干系统指标.