scholarly journals A Study of Service in Restaurant by Using Queuing Model

2013 ◽  
Vol 5 ◽  
pp. 14-18
Author(s):  
G.D. Mishra ◽  
Vijiya Singh Chauhan ◽  
Nikita Chandra
Keyword(s):  
Numerical Model ◽  
Waiting Time ◽  
Queuing Theory ◽  
Arrival Rate ◽  
Utilization Rate ◽  
Service Rate ◽  
Case Scenario ◽  
Queuing Model ◽  
Restaurant Management ◽  
Potential Customers

The restaurants want to avoid losing their customers due to a long wait on the line. This shows a need of a numerical model for the restaurant management to understand the situation better. This paper aims to show that queuing theory satisfies the model when tested with a real-case scenario. We obtained the data from a restaurant. We then derive the arrival rate, service rate, utilization rate, waiting time in queue and the probability of potential customers to balk based on the data using Little’s Theorem and M/M/1 queuing model. We conclude the paper by discussing the benefits of performing queuing analysis to a busy restaurant.

scholarly journals Application of queuing theory to a fast food outfit: a study of blue meadows restaurant

2017 ◽  
Vol 8 (2) ◽  
pp. 441 ◽  
Author(s):  
Seigha Gumus ◽  
Gordon Monday Bubou ◽  
Mobolaji Humphrey Oladeinde
Keyword(s):  
Waiting Time ◽  
Fast Food ◽  
Queuing Theory ◽  
Goodness Of Fit ◽  
Arrival Rate ◽  
Time Frame ◽  
Utilization Rate ◽  
Service Rate ◽  
Operating Characteristics ◽  
Number Of Customers

The study evaluated the queuing system in Blue Meadows restaurant with a view to determining its operating characteristics and to improve customers’ satisfaction during waiting time using the lens of queuing theory. Data was obtained from a fast food restaurant in the University of Benin. The data collected was tested to show if it follows a Poisson and exponential distribution of arrival and service rate using chi square goodness of fit. A 95% confidence interval level was used to show the range of customers that come into the system at an hour time frame and the range of customers served at an hour time frame. Using the M/M/s model, the arrival rate, service rate, utilization rate, waiting time in the queue and the probability of customers likely balking from the restaurant was derived. The arrival rate (λ) at Blue Meadows restaurant was about 40 customers per hour, while the service rate was about 22 customers per hour per server. The number of servers present in the system was two. The average number of customers in the system in an hour window was 40 customers with a utilization rate of 0.909. The paper concludes with a discussion on the benefits of performing queuing analysis to a restaurant.

Application of Queuing Theory to Address Traffic Problems at a Highway Toll Plaza

2014 ◽  
Vol 592-594 ◽  
pp. 2583-2587 ◽  
Author(s):  
Dheeraj Duhan ◽  
Nishant Arya ◽  
Prateek Dhanda ◽  
Lalit Upadhayay ◽  
K. Mathiyazhagan
Keyword(s):  
Data Analysis ◽  
Waiting Time ◽  
Traffic Congestion ◽  
Queuing Theory ◽  
Arrival Rate ◽  
North India ◽  
Service Rate ◽  
Operational Effectiveness ◽  
Toll Plazas ◽  
Toll Plaza

In India, due to the escalating traffic issues, a large number of highways have been built in the recent past, which are maintained by tax collection at toll plazas, by various operating agencies. Due to smooth and hassle free driving on highways, the arrival rate of vehicles at Toll Plazas increases. The arrival rate goes beyond control if the traffic on the highway increases in an uncontrolled manner, with the passage of time. Thus, one of the irrefutable drawbacks of putting up Toll Plazas, is the traffic congestion. The waiting time, in the service lanes, due to such a congestion becomes high and excruciating for the commuters on the route. The objective of this study is to analyze the current situation, of traffic congestion, at a highway toll plaza using queuing theory and suggest possible solutions to encourage greater efficiency, thus reducing waiting time of the customers and money wasted because of that. This study has been carried out in various phases, i.e. problem identification, data collection, data analysis and results at a selected Toll Plaza in North India. The data analysis in the study helps to find out the current operational effectiveness of the Toll Plaza through parameters like, Arrival Rate, Service Rate and Number of toll booths. Finally, possible solutions have been put forward which can be recommended and implemented on various Toll Plazas in the country.

scholarly journals Performance Modelling of Health-care Service Delivery in Adekunle Ajasin University, Akungba-Akoko, Nigeria Using Queuing Theory

2020 ◽  
pp. 119-127
Author(s):  
Orimoloye Segun Michael
Keyword(s):  
Health Care ◽  
Service Delivery ◽  
Queuing Theory ◽  
Health Care Service ◽  
Health Centre ◽  
Arrival Rate ◽  
Queuing System ◽  
Service Rate ◽  
Suitable Model ◽  
The Mean

The queuing theory is the mathematical approach to the analysis of waiting lines in any setting where arrivals rate of the subject is faster than the system can handle. It is applicable to the health care setting where the systems have excess capacity to accommodate random variation. Therefore, the purpose of this study was to determine the waiting, arrival and service times of patients at AAUA Health- setting and to model a suitable queuing system by using simulation technique to validate the model. This study was conducted at AAUA Health- Centre Akungba Akoko. It employed analytical and simulation methods to develop a suitable model. The collection of waiting time for this study was based on the arrival rate and service rate of patients at the Outpatient Centre. The data was calculated and analyzed using Microsoft Excel. Based on the analyzed data, the queuing system of the patient current situation was modelled and simulated using the PYTHON software. The result obtained from the simulation model showed that the mean arrival rate of patients on Friday week1 was lesser than the mean service rate of patients (i.e. 5.33> 5.625 (λ > µ). What this means is that the waiting line would be formed which would increase indefinitely; the service facility would always be busy. The analysis of the entire system of the AAUA health centre showed that queue length increases when the system is very busy. This work therefore evaluated and predicted the system performance of AAUA Health-Centre in terms of service delivery and propose solutions on needed resources to improve the quality of service offered to the patients visiting this health centre.

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

Modern Hypermarket Receiving Yard Utilization: The Implementation of a Simulation Model

2017 ◽  
Vol 2 (4) ◽  
pp. 33-39
Author(s):  
Mohammad Annas
Keyword(s):  
Simulation Model ◽  
Exponential Distribution ◽  
Poisson Distribution ◽  
Waiting Time ◽  
Arrival Rate ◽  
Jel Classification ◽  
Utilization Rate ◽  
Processing Times ◽  
Kolmogorov Smirnov ◽  
Using Data

Objective - This research is a direct observation of initial queuing, using data that is categorised into two clusters: the number of people queuing at busy hours, and processing times in the same circumstances. Methodology/Technique - The raw data was converted for use in the Poisson distribution test, as well as the Kolmogorov-Smirnov exponential distribution options. An arena simulation model was also applied to identify the vendor's waiting time and to analyse receiving yard utilization. The average waiting time according to the Poisson distribution, the average serving time per vendor by an exponential distribution, and the number of receiving yards, are all essential factors effecting the utilization of receiving yards. Findings - The study compares the length of queues, serving times, arrival rate, and time in the system using dual and single receiving yard systems. However, the utilization rate on a two receiving yards system is less than the rate on single receiving yard system. As the aim of this study is to identify the utilization rate of the receiving yard, a single receiving yard operation is more representative of modern hypermarkets, and more efficient in terms of resource efficiency. Novelty - This study depends fully on the homogeneous operating hours of the retailers' receiving yards, the type of vehicle used by vendors to unload merchandises, procedures on moving the products to the inspections phase, a generalization of the products delivered by the vendors and the size of the modern hypermarkets business itself. Type of Paper: Empirical. Keywords: Receiving Yard Utilization; Hypermarket Receiving Yard; Queuing Simulation. JEL Classification: M1, M10, M19.

Minimum carbon dioxide emission based selection of traffic route with unsignalised junctions in tandem network

2019 ◽  
Vol 30 (3) ◽  
pp. 657-675 ◽  
Author(s):  
Anand Jaiswal ◽  
Cherian Samuel ◽  
Chirag Chandan Mishra
Keyword(s):  
Carbon Dioxide ◽  
Queuing Theory ◽  
Mathematical Formulation ◽  
Carbon Dioxide Emission ◽  
Arrival Rate ◽  
Selection Strategy ◽  
Service Rate ◽  
Content Type ◽  
Fuel Consumption Rate ◽  
Route Choices

Purpose The purpose of this paper is to provide a traffic route selection strategy based on minimum carbon dioxide (CO2) emission by vehicles over different route choices. Design/methodology/approach The study used queuing theory for Markovian M/M/1 model over the road junctions to assess total time spent over each of the junctions for a route with junctions in tandem. With parameters of distance, mean service rate at the junction, the number of junctions and fuel consumption rate, which is a function of variable average speed, the CO2 emission is estimated over each of the junction in tandem and collectively over each of the routes. Findings The outcome of the study is a mathematical formulation, using queuing theory to estimate CO2 emissions over different route choices. Research finding estimated total time spent and subsequent CO2 emission for mean arrival rates of vehicles at junctions in tandem. The model is validated with a pilot study, and the result shows the best vehicular route choice with minimum CO2 emissions. Research limitations/implications Proposed study is limited to M/M/1 model at each of the junction, with no defection of vehicles. The study is also limited to a constant mean arrival rate at each of the junction. Practical implications The work can be used to define strategies to route vehicles on different route choices to reduce minimum vehicular CO2 emissions. Originality/value Proposed work gives a solution for minimising carbon emission over routes with unsignalised junctions in the tandem network.

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.

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%.

scholarly journals Optimization of Markov Queuing Model in Hospital Bed Resource Allocation

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Jingna Wu ◽  
Bo Chen ◽  
Danping Wu ◽  
Jianqiang Wang ◽  
Xiaodong Peng ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Queuing Theory ◽  
Health Resources ◽  
Utilization Rate ◽  
Scientific Management ◽  
Queuing Model ◽  
Steady State Probability ◽  
Advantages And Disadvantages ◽  
Hospital Bed ◽  
The Individual

Bed resources are the platform in which most medical and health resources in the hospital play a role and carry the core functions of the health service system. How to improve the efficiency of the use of bed resources through scientific management measures and methods and ultimately achieve the optimization of overall health resources is the focus of hospital management teams. This paper analyzes the previous research models of knowledge related to queuing theory in medical services. From the perspective of the hospital and the patient, several indicators such as the average total number of people, the utilization rate of bed resources, the patient stop rate, and the patient average waiting time are defined to measure the performance of the triage queue calling model, which makes the patient queue more reasonable. According to the actual task requirements of a hospital, a Markov queuing strategy based on Markov service is proposed. A mathematical queuing model is constructed, and the process of solving steady-state probability based on Markov theory is analyzed. Through the comparative analysis of simulation experiments, the advantages and disadvantages of the service Markov queuing model and the applicable scope are obtained. Based on the theory of the queuing method, a queuing network model of bed resource allocation is established in principle. Experimental results show that the queuing strategy of bed resource allocation based on Markov optimization effectively improves resource utilization and patient satisfaction and can well meet the individual needs of different patients. It does not only provide specific optimization measures for the object of empirical research but also provides a reference for the development of hospital bed resource allocation in theory.

Optimization of Queuing Theory Based on Vague Environment

2016 ◽  
Vol 5 (1) ◽  
pp. 1-26 ◽  
Author(s):  
Verónica Andrea González-López ◽  
Ramin Gholizadeh ◽  
Aliakbar M. Shirazi
Keyword(s):  
Everyday Life ◽  
Real World ◽  
Queuing Theory ◽  
Arrival Rate ◽  
Service Rate ◽  
New Approach ◽  
The Real ◽  
Processing Times ◽  
Queuing Models ◽  
Service Rates

Waiting lines or queues are commonly occurred both in everyday life and in a variety of business and industrial situations. The various arrival rates, service rates and processing times of jobs/tasks usually assumed are exact. However, the real world is complex and the complexity is due to the uncertainty. The queuing theory by using vague environment is described in this paper. To illustrate, the approach analytical results for M/M/1/8 and M/M/s/8 systems are presented. It optimizes queuing models such that the arrival rate and service rate are vague numbers. This paper results a new approach for queuing models in the vague environment that it can be more effective than deterministic queuing models. A numerical example is illustrated to check the validity of the proposed method.

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