scholarly journals A bulk queueing system under N-policy with bilevel service delay discipline and start-up time (Erratum)

1994 ◽  
Vol 7 (2) ◽  
pp. 207-207 ◽  
Author(s):  
David C. R. Muh
Keyword(s):  
Queueing System ◽  
Service Delay ◽  
Start Up

scholarly journals A bulk queueing system under N-policy with bilevel service delay discipline and start-up time

1993 ◽  
Vol 6 (4) ◽  
pp. 359-384 ◽  
Author(s):  
David C. R. Muh
Keyword(s):  
Queue Length ◽  
Queueing System ◽  
Probability Generating Function ◽  
Single Server ◽  
Numerical Examples ◽  
Queueing Process ◽  
Poisson Input ◽  
Service Delay ◽  
Start Up ◽  
Bulk Arrival

The author studies the queueing process in a single-server, bulk arrival and batch service queueing system with a compound Poisson input, bilevel service delay discipline, start-up time, and a fixed accumulation level with control operating policy. It is assumed that when the queue length falls below a predefined level r(≥1), the system, with server capacity R, immediately stops service until the queue length reaches or exceeds the second predefined accumulation level N(≥r). Two cases, with N≤R and N≥R, are studied.The author finds explicitly the probability generating function of the stationary distribution of the queueing process and gives numerical examples.

scholarly journals First passage processes in Queuing systemMX/Gr/1with service delay discipline

1994 ◽  
Vol 17 (3) ◽  
pp. 571-586
Author(s):  
Lev Abolnikov ◽  
Jewgeni H. Dshalalow ◽  
Alexander M. Dukhovny
Keyword(s):  
Queueing System ◽  
Sufficient Conditions ◽  
Compound Poisson Process ◽  
Single Server ◽  
Input Stream ◽  
Service Delay ◽  
Semi Markov Process ◽  
Necessary And Sufficient ◽  
Queueing Processes ◽  
Steady State Probabilities

This article deals with a general single-server bulk queueing system with a server waiting until the queue will reach levelrbefore it starts processing customers. If at leastrcustomers are available the server takes a batch of the fixed sizerof units for service. The input stream is assumed to be a compound Poisson process modulated by a semi-Markov process and with a multilevel control of service time.The authors evaluate the steady state probabilities of the queueing processes with discrete and continuous time parameter preliminarily establishing necessary and sufficient conditions for the ergodicity of the processes. The authors use the recent results on the first excess level processes to explicitly find all characteristics of the named processes. Some characteristics of the input process, service cycle, intensity of the system, and both idle and busy periods are also found. The results obtained in the article are illustrated by numerous examples.

scholarly journals A first passage problem and its applications to the analysis of a class of stochastic models

1992 ◽  
Vol 5 (1) ◽  
pp. 83-97 ◽  
Author(s):  
Lev Abolnikov ◽  
Jewgeni H. Dshalalow
Keyword(s):  
Inventory Control ◽  
Stochastic Models ◽  
Queueing System ◽  
Queueing Systems ◽  
First Passage ◽  
Numerical Examples ◽  
Fixed Level ◽  
Service Delay ◽  
Probability Methods ◽  
First Passage Problem

A problem of the first passage of a cumulative random process with generally distributed discrete or continuous increments over a fixed level is considered in the article as an essential part of the analysis of a class of stochastic models (bulk queueing systems, inventory control and dam models).Using direct probability methods the authors find various characteristics of this problem: the magnitude of the first excess of the process over a fixed level, the shortage before the first excess, the levels of the first and pre-first excesses, the index of the first excess and others. The results obtained are illustrated by a number of numerical examples and then are applied to a bulk queueing system with a service delay discipline.

scholarly journals Transient Analysis of M[X1],M[X2]/G1,G2/1 retrial queueing system with priority services, working breakdown, start up/close down time, Bernoulli vacation, reneging and balking

2020 ◽  
pp. 203-216
Author(s):  
Govindhan Ayyappan ◽  
Udayageetha J
Keyword(s):  
Transient Analysis ◽  
Queueing System ◽  
Variable Technique ◽  
Retrial Queueing System ◽  
System A ◽  
Retrial Queueing ◽  
Start Up ◽  
Set Up ◽  
Number Of Customers ◽  
Bernoulli Vacation

This paper considers  M[X1],M[X2]/G1,G2/1 general retrial queueing system with priority services. Two types of customers from different classes arrive at the system in different independent compound Poisson processes. The server follows the pre-emptive priority rule subject to working breakdown, startup/closedown time and Bernoulli vacation with general (arbitrary) vacation periods. After completing the service, if there are no priority customers present in the system the server may go for a vacation or close down the system. On completion of the close down, the server needs some time to set up the system. The priority customers who find the server busy are queued in the system. A low-priority customer who find the server busy are routed to a retrial (orbit) queue that attempts to get the service. The system may breakdown at any point of time when it is in operation. However, when the system fails, instead of stopping service completely, the service is continued only to the high priority customers at a slower rate. We consider balking to occur to the low priority customer while the server is busy or idle, and reneging to occur at the high priority customers during server’s vacation, start up/close down time. Using the supplementary variable technique, we derive the joint distribution of the server state and the number of customers in the system. Finally, some performance measures and numerical examples are presented.

scholarly journals Implementation of The Open Jackson Queuing Network to Reduce Waiting Time

2020 ◽  
Vol 6 (2) ◽  
pp. 83-92
Author(s):  
Monike Febriyani Faris ◽  
Yuniar Farida ◽  
Dian C. Rini Novitasari ◽  
Nurissaidah Ulinnuha ◽  
Moh. Hafiyusholeh
Keyword(s):  
Waiting Time ◽  
Queueing System ◽  
Waiting Times ◽  
Queueing Network ◽  
Hospital Services ◽  
Queuing Network ◽  
Service Delay ◽  
Patient Will ◽  
Queue Network Model

Waiting for service is a common thing in-hospital services. The more patients are waiting, the service delay increases, so waiting time in the queue gets longer. In health care in a hospital, a patient will queue several times in more than one queue in a hospital outpatient installation. The case study in this research is the queue system in the hospital's outpatient treatment, implementing an open Jackson queueing network to minimize waiting time. The workstations examined in this study were the registration, pre-consultation, and cardiology poly consultation, and pharmacy. The data is carried out for six days, counting the number of arrivals and departures with each point at intervals of 5 minutes. Applying the Jackson open queue network model, a recommendation was obtained for the hospital to increase employees' numbers. The registration workstation must have four servers; a poly cardiology workstation had three nurses and four doctors, while for pharmacy, had seven employees. With this personnel's addition, patients' total waiting time in the queuing system is approximately 12 minutes/patient. So, it can reduce waiting times in the queueing system that was initially 108 minutes/patient.

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