scholarly journals Control Chart for Waiting Time in System of (M / M / 1) :( ? / FCFS) Queuing Model

2013 ◽  
Vol 63 (3) ◽  
pp. 1-6
Author(s):  
T. Poongodi ◽  
S. Muthulakshmi
Keyword(s):  
Control Chart ◽  
Waiting Time ◽  
Queuing Model

scholarly journals Applications of Queuing Theory in Quantitative Business Analysis

2020 ◽  
pp. 253-257
Keyword(s):  
Quantitative Analysis ◽  
Waiting Time ◽  
Queuing Theory ◽  
Single Channel ◽  
Analysis Approach ◽  
Single Server ◽  
Expected Number ◽  
Queuing Model ◽  
Infinite Population ◽  
Expected Waiting Time

Queuing Theory provides the system of applications in many sectors in life cycle. Queuing Structure and basic components determination is computed in queuing model simulation process. Distributions in Queuing Model can be extracted in quantitative analysis approach. Differences in Queuing Model Queue discipline, Single and Multiple service station with finite and infinite population is described in Quantitative analysis process. Basic expansions of probability density function, Expected waiting time in queue, Expected length of Queue, Expected size of system, probability of server being busy, and probability of system being empty conditions can be evaluated in this quantitative analysis approach. Probability of waiting ‘t’ minutes or more in queue and Expected number of customer served per busy period, Expected waiting time in System are also computed during the Analysis method. Single channel model with infinite population is used as most common case of queuing problems which involves the single channel or single server waiting line. Single Server model with finite population in test statistics provides the Relationships used in various applications like Expected time a customer spends in the system, Expected waiting time of a customer in the queue, Probability that there are n customers in the system objective case, Expected number of customers in the system

scholarly journals Analysis of queue change of visitors and performace system in the Department of Population and Civil Regristation of Semarang City

2020 ◽  
Vol 202 ◽  
pp. 15005
Author(s):  
Sugito ◽  
Alan Prahutama ◽  
Dwi Ispriyanti ◽  
Mustafid
Keyword(s):  
Customer Satisfaction ◽  
Waiting Time ◽  
Public Service ◽  
Service Time ◽  
Service Sector ◽  
General Distribution ◽  
Queuing Systems ◽  
Queuing Model ◽  
The Public ◽  
Second Period

The Population and Civil Registry Office in Semarang city is one of the public service units. In the public service sector, visitor / customer satisfaction is very important. It can be identified by the length of the queue, the longer visitors queue this results in visitor dissatisfaction with the service. Queue analysis is one of the methods in statistics to determine the distribution of queuing systems that occur within a system. In this study, a queuing analysis as divided into two periods. The first period lasts from 2-13 March 2015, while the second period lasts November 16th to December 20th 2019. The variables used are the number of visitors and the service time at each counter in intervals of 30 minutes. The results obtained are changes in the distribution and queuing model that is at counter 5/6 and counter 10. The queuing model obtained at the second perideo for the number of visitors and the time of service with a General distribution. The average number of visitors who come in 30 minute intervals in the second period is more than the first period, this indicates an increase in visitors. The opportunity for service units is still small, the waiting time in the queue is getting smaller. This shows that the performance of the queuing system at the Semarang Population and Civil Registry Office is getting better.

scholarly journals Optimization Design of X-ray Conveyer Belt Length for Subway Security Check Systems in Beijing, China

2020 ◽  
Vol 12 (5) ◽  
pp. 2133 ◽  
Author(s):  
Zhonghua Wei ◽  
Sinan Chu ◽  
Zhengde Huang ◽  
Shi Qiu ◽  
Qixuan Zhao
Keyword(s):  
Waiting Time ◽  
Optimization Design ◽  
Arrival Rate ◽  
Conveyer Belt ◽  
Modeling Framework ◽  
Queuing Model ◽  
X Ray ◽  
Potential Safety ◽  
Subway Stations ◽  
Security Check

The frequent terrorist attacks in subways has dramatically increased the necessity and importance of security check systems (SCSs). The implementation of a SCS in China has successfully eliminated lots of potential safety hazards. However, the excessive waiting time due to the SCS is also an issue. SCS efficiency is greatly affected by the length of the conveyer belt of the X-ray machine (CBXM). A scheme for optimizing the CBXM length to accommodate different passenger flows is proposed in this paper. A modeling framework is developed for associating the CBXM length with the queuing waiting time based on a M/M/1/N queuing model. The optimal scheme of CBXM length calculated from the model demonstrates that the passenger queuing time is saved by 15.7%, 16.0%, and 23.3% with the passenger arrival rate of 4000, 5000, and 6000, respectively, greatly reducing queuing crowdedness. The scheme can be used to select X-ray machines for subway stations by their passenger arrival rates. In addition, the findings of this paper could be a crucial supplement and perfect the design code of subway SCSs.

Enjoyable queuing and waiting time

2017 ◽  
Vol 28 (2) ◽  
pp. 543-566 ◽  
Author(s):  
Chih-Chin Liang
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Waiting Time ◽  
Structural Equation ◽  
Group Analysis ◽  
Customer Experience ◽  
Consumer Electronics ◽  
Equation Modeling ◽  
Queuing Model ◽  
Customer Perceptions

Time theory studies abstractly argue that, depending on the customer experience, time spent waiting may be positive, negative, or even neutral, and it can affect the perceived passing of time and enjoyment of the overall customer experience. However, a company can manipulate customer perceptions of waiting time. Positive perceptions of waiting time can then be used for marketing purposes. Customer perceptions of waiting time can be reduced by making the queuing process enjoyable, by improving the waiting environment, and by making promotional activities enjoyable. To validate the aforementioned factors and develop the enjoyable queuing model, this study surveyed 1571 customers queuing at service companies in Taiwan, including 409 customers of upscale restaurants, 430 customers of restaurants, 439 customers of food stands, and 293 customers queuing at consumer electronics shops to purchase newly released iPhones. The applicability of the enjoyable queuing model was evaluated by partial least squares structural equation modeling, and group differences were evaluated by partial least squares multi-group analysis. The analytical results for each case and managerial implications are presented.

A Hybrid Multiple Parallel Queuing Model to Enhance QoS in Cloud Computing

2020 ◽  
Vol 12 (1) ◽  
pp. 18-34 ◽  
Author(s):  
Shahbaz Afzal ◽  
G. Kavitha
Keyword(s):  
Cloud Computing ◽  
Response Time ◽  
Waiting Time ◽  
Queue Length ◽  
Utilization Rate ◽  
Queuing Model ◽  
Total Response Time ◽  
Proposed Model ◽  
Mathematical Equations ◽  
And Performance

Among the different QoS metrics and parameters considered in cloud computing are the waiting time of cloud tasks, execution time of tasks in VM's, and the utilization rate of servers. The proposed model was developed to overcome some of the pitfalls in the existing systems among which are sub-optimal markdown in the queue length, waiting time, response time, and server utilization rate. The proposed model contemplates on the enhancement of these metrics using a Hybrid Multiple Parallel Queuing approach with a joint implementation of M/M/1: ∞ and M/M/s: N/FCFS to achieve the desired objectives. A neoteric set of mathematical equations have been formulated to validate the efficiency and performance of the hybrid queuing model. The results have been validated with reference to the workload traces of Bit Brains infrastructure provider. The results obtained indicate the significant reduction in the queue length by 60.93 percent, waiting time in the queue by 73.85 percent, and total response time by 97.51%.

Development of a Heuristics Model for Simplifying a Multi-Channel Queuing System

2011 ◽  
Vol 367 ◽  
pp. 647-652
Author(s):  
B. Kareem ◽  
A. A. Aderoba
Keyword(s):  
Waiting Time ◽  
Channel Model ◽  
Single Channel ◽  
Queuing System ◽  
Queuing Model ◽  
Average Waiting Time ◽  
Queuing Models ◽  
Significant Difference ◽  
Number Of Customers ◽  
Proportionality Principle

Queuing model has been discussed widely in literature. The structures of queuing systems are broadly divided into three namely; single, multi-channel, and mixed. Equations for solving these queuing problems vary in complexity. The most complex of them is the multi-channel queuing problem. A heuristically simplified equation based on relative comparison, using proportionality principle, of the measured effectiveness from the single and multi-channel models seems promising in solving this complex problem. In this study, six different queuing models were used from which five of them are single-channel systems while the balance is multi-channel. Equations for solving these models were identified based on their properties. Queuing models’ performance parameters were measured using relative proportionality principle from which complexity of multi-channel system was transformed to a simple linear relation of the form = . This showed that the performance obtained from single channel model has a linear relationship with corresponding to multi-channel, and is a factor which varies with the structure of queuing system. The model was tested with practical data collected on the arrival and departure of customers from a cocoa processing factory. The performances obtained based on average number of customers on line , average number of customers in the system , average waiting time in line and average waiting time in the system, under certain conditions showed no significant difference between using heuristics and analytical models.

scholarly journals A queuing model to address waiting time inconsistency in solid-organ transplantation

2014 ◽  
Vol 3 (1) ◽  
pp. 40-45 ◽  
Author(s):  
David A. Stanford ◽  
Jung Min Lee ◽  
Natasha Chandok ◽  
Vivian McAlister
Keyword(s):  
Organ Transplantation ◽  
Waiting Time ◽  
Solid Organ Transplantation ◽  
Time Inconsistency ◽  
Solid Organ ◽  
Queuing Model

scholarly journals M/M/C Queue under Monte Carlo Simulation for a Restaurant Model

2019 ◽  
Vol 8 (10) ◽  
pp. 1818-1823
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Waiting Time ◽  
Analytical Methods ◽  
Queuing Model ◽  
Stationary Density ◽  
Density Flow ◽  
The Future

In this paper we present a stochastic queuing model for a restaurant which captures the stationary density flow relations. The performance of controlling the heterogeneous crowd in a restaurant under Monte Carlo simulation with various service distributions has been discussed. Using this analysis in future the waiting time of the customers can be reduced and the profit of the management can also be increased. The future behaviour of a restaurant networks both in simulation and analytical methods have been analysed.

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