scholarly journals Numerical of A Call Centre with Two Types of Queue

2019 ◽  
Vol 9 (1) ◽  
pp. 3260-3262
Keyword(s):  
Joint Distribution ◽  
Geometric Method ◽  
Call Centre ◽  
Numerical Examples ◽  
Queue System ◽  
Matrix Geometric Method ◽  
Queue Model

Call centre is modelled as a queue system with invisible queue and virtual queue. It forms a special type of structured level dependent matrix. Matrix geometric method is used to find the time independent joint distribution of number of invisible customers and visible customers. Through numerical examples we have given the comparison between the existing call centre queue model and the model that we have proposed.

scholarly journals Queues with two units connected in series with a multiserver bulk service with accessible and non accessible batch in unit II

2014 ◽  
Vol 4 (1) ◽  
Author(s):  
G. Ayyappan ◽  
S. Velmurugan
Keyword(s):  
Service Time ◽  
Subject Classification ◽  
Geometric Method ◽  
Finite Buffer ◽  
Queueing Model ◽  
Service Station ◽  
Matrix Geometric Method ◽  
In Series ◽  
Bulk Service ◽  
Number Of Customers

This paper analyses a queueing model consisting of two units I and II connected in series, separated by a finite buffer of size N. Unit I has only one exponential server capable of serving customers one at a time. Unit II consists of c parallel exponential servers and they serve customers in groups according to the bulk service rule. This rule admits each batch served to have not less than ‘a’ and not more than ‘b’ customers such that the arriving customers can enter service station without affecting the service time if the size of the batch being served is less than ‘d’ ( a ≤ d ≤ b ). The steady stateprobability vector of the number of customers waiting and receiving service in unit I and waiting in the buffer is obtained using the modified matrix-geometric method. Numerical results are also presented. AMS Subject Classification number: 60k25 and 65k30

scholarly journals PENENTUAN MODEL ANTREAN NON-POISSON DAN PENGUKURAN KINERJA PELAYANAN BUS RAPID TRANSIT TRANS SEMARANG (STUDI KASUS: SHELTER PEMBERANGKATAN BRT KORIDOR V)

2021 ◽  
Vol 10 (1) ◽  
pp. 1-10
Author(s):  
Purwati Ayuningtyas ◽  
Sugito Sugito ◽  
Di Asih I Maruddani
Keyword(s):  
Service System ◽  
Bus Rapid Transit ◽  
Load Factor ◽  
Rapid Transit ◽  
Operational Effectiveness ◽  
Value System ◽  
Queue System ◽  
Transportation Service ◽  
Queue Model ◽  
Queue Theory

One of the queue systems that is often found  in daily life is the transportation service system, for example a queue system at the shelters departure of corridor V Bus Rapid Transit (BRT) Trans Semarang. Corridor V has three departure shelters, they are Shelter Victoria Residence, Shelter Marina, and Shelter Bandara Ahmad Yani. Corridor V was choosen, because of its high load factor on January to June 2019. Based on the observation, the service time at the departure shelter is usually longer than the normal shelter. This causes the rise of queue at the departure shelters. The queue at the departure shelters can hamper the arrival of BRT at the other shelters, so the application of the queue theory is needed to find out the extent of operational effectiveness at the departure shelters. The resulting queue model is the Non-Poisson queue model, the queue model for Victoria Residence Shelter: (DAGUM/GEV/1):(GD/∞/∞), Marina Shelter: (DAGUM/G/1):(GD/∞/∞), and Bandara Ahmad Yani Shelter: (GEV/GEV/1):(GD/∞/∞). Based on the value from measurement of the queue system performance, it can be conclude that the three departure shelters of corridor V BRT Trans Semarang have some optimal condition. Keywords: Shelter Departure of Corridor V, Non-Poisson Queueing Model, Dagum, Generalized Extreme Value, System Perfomance Measure  

scholarly journals Batch Arrival Queueing Model with Unreliable Server

2018 ◽  
Vol 7 (4.10) ◽  
pp. 269 ◽  
Author(s):  
M. Seenivasan ◽  
K. S.Subasri
Keyword(s):  
Queue Length ◽  
Queuing System ◽  
Subject Classification ◽  
Geometric Method ◽  
Batch Arrival ◽  
Queueing Model ◽  
Unreliable Server ◽  
Matrix Geometric Method

The unreliable server with provision of temporary server in the context of application has been investigated. A temporary server is installed when the primary server is over loaded i.e., a fixed queue length of K-policy customers including the customer with the primary server has been build up. The primary server may breakdown while rendering service to the customers; it is sent for the repair. This type of queuing system has been investigated using Matrix Geometric Method to obtain the probabilities of the system steady state.AMS subject classification number— 60K25, 60K30 and 90B22.  

scholarly journals A simple integer-valued bilinear time series model

2006 ◽  
Vol 38 (2) ◽  
pp. 559-578 ◽  
Author(s):  
P. Doukhan ◽  
A. Latour ◽  
D. Oraichi
Keyword(s):  
Time Series ◽  
Method Of Moments ◽  
Joint Distribution ◽  
Time Series Data ◽  
Stationary Process ◽  
Existence Condition ◽  
Series Data ◽  
Bilinear Model ◽  
Numerical Examples ◽  
Strictly Stationary Process

In this paper, we extend the integer-valued model class to give a nonnegative integer-valued bilinear process, denoted by INBL(p,q,m,n), similar to the real-valued bilinear model. We demonstrate the existence of this strictly stationary process and give an existence condition for it. The estimation problem is discussed in the context of a particular simple case. The method of moments is applied and the asymptotic joint distribution of the estimators is given: it turns out to be a normal distribution. We present numerical examples and applications of the model to real time series data on meningitis and Escherichia coli infections.

Analysis of a two-queue model with Bernoulli schedules

1997 ◽  
Vol 34 (1) ◽  
pp. 176-191 ◽  
Author(s):  
Duan-Shin Lee
Keyword(s):  
Integral Equation ◽  
Boundary Value Problem ◽  
Queueing System ◽  
Boundary Value ◽  
Single Server ◽  
Riemann Boundary Value Problem ◽  
Riemann Boundary ◽  
Numerical Examples ◽  
Special Cases ◽  
Queue Model

In this paper we analyze a single server two-queue model with Bernoulli schedules. This discipline is very flexible and contains the exhaustive and 1-limited disciplines as special cases. We formulate the queueing system as a Riemann boundary value problem with shift. The boundary value problem is solved by exploring a Fredholm integral equation around the unit circle. Some numerical examples are presented at the end of the paper.

scholarly journals Analisis Proses Produksi Menggunakan Teori Antrian Secara Analitik dan Simulasi

2019 ◽  
Vol 8 (1) ◽  
pp. 9-18
Author(s):  
Rika Listiyani ◽  
Lilik Linawati ◽  
Leopoldus Ricky Sasongko
Keyword(s):  
Waiting Time ◽  
Service Time ◽  
Simulation Analysis ◽  
Queuing System ◽  
Queue System ◽  
Performance Improvements ◽  
Service Production ◽  
Significant Difference ◽  
Queue Model ◽  
Simulation Results

The focus of this research is to analyze the production process queuing system at one of the stages of production of swiftlet nest in analytical and simulation. The purpose of this research is to obtain the model and characteristics of the queue system at the Finishing-2. The analysis uses data on the rate of arrival and the rate of service based on real observation and determines the probability distribution of data between arrival time and service time using the Easyfit 3.0 program, to get the model of the queuing system is obtained. After the model obtained, analytic and simulation analysis is carried out using the Queuing System Simulation (QSS) module in the WINQSB software. The results of the queuing system characteristics in the analytical and simulation have a significant difference, because the distribution of time between arrivals and service times used in analytical calculations is G (general), while the simulation uses a distribution that refers to a particular type of distribution according to the results of the Easyfit program. Simulation is carried out with the FIFO and SIRO queue disciplines. The simulation results show that 91% of the characteristics of the queue system in the two queue disciplines do not have a significant difference. Moreover, it has also been done a comparison between the characteristics of the queuing system in two different work areas namely Room A and Room B&C, based on the simulation results, the results show 58% of the characteristics of the queuing system have a significant difference, this is due to differences in service time between the two work areas. Thus the purpose of this research has been achieved which is obtained by the queue model (G/G/c):(FIFO/∞/∞), and also obtained system performance improvements, in the form of waiting time in the queue where the waiting time in Room B&C is smaller than Room A. Keywords: Queuing, Arrival, Service, Production, Simulation.

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