Periodicity.: April - June 2017
e-ISSN......: 2236-269X
Cover Image

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

Seigha Gumus, Gordon Monday Bubou, Mobolaji Humphrey Oladeinde

Abstract


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.


Keywords


queuing theory; Poisson distribution; service rate; customer satisfaction; fast food outfit; Blue Meadows Restaurant

Full Text:

PDF HTML

References


ANDREWS, B.; PARSONS, H. (1993) Establishing telephone-agent staffing levels through economic optimization. Interfaces, v. 23, p. 14-20.

AUTY, S. (1992) Consumer choice and segmentation in the restaurant industry. The Service Industries Journal, v. 12, n. 3, p. 324-339.

BRANN, D. M.; KULICK, B. C. (2002) Simulation of restaurant operations using the Restaurant Modeling Studio. In: WINTER SIMULATION CONFERENCE, proceedings... IEEE Press, December, p. 1448-1453.

CHOWDHURRY, M. S. R. (2013) Queuing theory model used to solve the waiting line of a bank – a study on Islami Bank Bangladesh Limited, Chawkbazar Branch, Chittagong. Asian Journal of Social Sciences and Humanities, v. 2, n. 3, p. 468-478.

COOPER, R. B. (1990) “Queueing Theory”. In HEYMAN, D. P.; SOBEL, M. J. (Ed.) Stochastic Models, Amsterdam: North-Holland (Elsevier), p. 469-518.

COPE, R. F.; COPE III, R. F.; BASS, A. N.; SYRDAL, H. A. (2011) Innovative knowledge management at Disney: human capital and queuing solutions for services. Journal of Service Science, v. 4, n. 1, p. 1-20.

CURIN, S. A.; VOSKO, J. S.; CHAN, E. W.; TSIMHONI, O. (2005) Reducing service time at a busy fast food restaurant on campus. In: WINTER SIMULATION CONFERENCE, proceedings… IEEE Press, December.

DHARMAWIRYA, M.; ADI, E. (2011) Case study for restaurant queuing model. In: International Conference On Management And Artificial Intelligence, IPEDR, Bali: IACSIT Press, n. 6, p. 52-55.

JONES, P.; DENT, M. (1994) Improving service: Managing response time in hospitality operations. International Journal of Operation and Production Management, v. 14, p. 52-8.

KAVITHA, J.; PALANIAMMAL, S. (2014) Efficient path selection and data transmission using queue in open shortest path first. International Journal of Computer Science and Application, v. 3, n. 4, p. 139-144. Available: http://www.ij‐csa.org. Access: 4th November, 2016. DOI: 10.14355/ijcsa.2014.0304.01.

KENDALLl, D. G. (1953) Stochastic processes occurring in the theory of queues and their analysis by the method of the Imbedded Markov Chain. The Annals of Mathematical Statistics. v. 24, n. 3, p. 338-354. DOI: 10.1214/aoms/1177728975.

NOSEK, R. A.; WILSON, J. P. (2001). Queuing theory and customer satisfaction: a review of terminology, trends, and applications to pharmacy practice. Hospital Pharmacy, v. 36, n. 3, p. 275-279.

KHARWAT, A. K. (1991). Computer simulation: an important tool in the fast-food industry. In: Winter Simulation Conference, proceedings… IEEE Press, p. 811-815.

LI, L.; LEE, Y. S. (1994). Pricing and delivery-time performance in a competitive environment. Management Science, v. 40, n. 5, p. 633-646.

MANDIA, S., (2009) Design of Queuing System, Department of Mechanical and Industrial Engineering.

OLADEJO, M. O.; AGASHUA, N. U.; TAMBER, J. A. (2015) Optimizing the queuing system of a fast food restaurant: a case study of Ostrich Bakery. International Journal of Development in Engineering and Technology, v. 4, n. 8, p. 7-15.

PIERCE (II), R. A.; ROGERS E. M.; SHARP, M. H. (1990) Outpatient pharmacy redesign to improve workflow, waiting time, and patient satisfaction. American Journal of Hospital Pharmacy, v. 47, p. 351-6.

PROCTOR, R. A. (1994). Queues and the power of simulation: helping with business decisions and problems. Management Decisions, v. 32, p. 50-5.

RAMAKRISHNA, R.; MOHAMEDHUSIEN, K. (2015) Simulation technique for queuing theory: a case study. International Journal of Research and Applications, v. 2, n. 8, p. 388-396.

ROSENFELD, M. (1997). Arlington DMV’s speedy service: new system eliminates long lines. The Washington Post, August 8:A1, A17

SHARMA, J. K. (2010) Operations Research: Theory and Applications 4. ed. New Delhi: MacMillan Publishers.

SOMANI, S. M.; DANIELS, C. E.; JERMSTAD, R. L. (1982) Patient satisfaction with outpatient pharmacy services. American Journal of Hospital Pharmacy, v. 39, p. 1025-1027.

SZTRIK, J. (2010) Queueing theory and its applications: a personal view. In: The 8th International Conference On Applied Informatics, proceedings… Eger Hungary, v. 1, p. 9-30.

TYAGI, A.; SAROA, M. S.; SINGH, T. P. (2014) Application of Stochastic Queue Model in a Restaurant – A case Study. Aryabhatta Journal of Mathematics and Informatics, v. 6, n. 1, p. 115-118.

YAKUBU, A. N.; NAJIM, U. (2014) An application of queuing theory to ATM service optimization: a case study. Mathematical Theory and Modeling, v. 4, n. 6, p. 11-23.

ZHANG, L. J.; NG, W. W. J. L.; TAY, S. C. (2000) Discrete–event simulation of queuing systems. The Sixth Youth Science Conference, Ministry of Education, Singapore, p. 1–2.




DOI: http://dx.doi.org/10.14807/ijmp.v8i2.576

Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM

Refbacks



Copyright (c) 2017 Seigha Gumus, Gordon Monday Bubou

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

LIBRARIES BY

Logo Gaudeamus

Logo INDIANA

Logo CHENG KUNG

Logo UTEP

Logo MOBIUS

Logo UNIVEM

Logo Kennedy

Logo Columbia

Logo UCS

Logo MSG/UFF

Logo OPT

Logo Biblioteca Professor Milton Cabral Moreira

Logo UFL

Logo ULRICHSWEB

Logo UNISA