The Impact of the Constraints of Class Scheduling on Campus Dining: A Simulation-based Case Study

  • Jeremiah Ivan ,
  • Steven Rooney,
  • Hunter Carlson,
  • Spencer Bentley,
  • e  Derek Fisher,
  • Anastasia Angelopoulou
  • a,b,c,d,e  Embry-Riddle Aeronautical University, 3700 Willow Creek Rd, Prescott, AZ 86301Embry-Riddle Aeronautical University
  • Columbus State University, 4225 University Ave, Columbus, GA, 31907, USA
Cite as
Ivan J., Rooney S., Carlson H., Bentley S., Fisher D., Angelopoulou A. (2021). The Impact of the Constraints of Class Scheduling on Campus Dining: A Simulation-based Case Study. Proceedings of the 33rd European Modeling & Simulation Symposium (EMSS 2021), pp. 266-271. DOI:


Waiting in queues in service systems is an inevitable part of the customer’s everyday routine. Waiting time is an important indicator of a service system’s performance. This paper studies the efficiency of service operations in a college campus dining setting. The authors implemented a discrete event simulation (DES) model in Simio to study how class scheduling may affect the overall customer waiting time and satisfaction at the college campus dining location. The results provide recommendations on how classes could be scheduled to optimize students’ satisfaction with their lunchtimes and the quality of service. The results also provide valuable insights for operating during the COVID-19 pandemic, as campus dining locations have a decreased maximum capacity, which may lead to more bottlenecks than usual and increase waiting times.


  1. Ahsan, M. M., Islam, M. R., & Alam, M. A. (2014). Study of queuing system of a busy restaurant and a proposed facilitate queuing system. IOSR Journal of Mechanical and Civil Engineering, 11(6), 31-35. 
  2. Bielen, F. & Demoulin, N. (2007). Waiting time influence on the satisfaction-loyalty relationship in services, Managing Service Quality: An International Journal, Vol. 17 No. 2, pp. 174-193.
  3. Dharmawirya, M., Oktadiana, H., & Adi, E. (2012). Analysis of expected and actual waiting time in fast-food restaurants. Industrial Engineering Letters, 2(5). 
  4. Law, A. K., Hui, Y. V., & Zhao, X. (2004). Modeling repurchase frequency and customer satisfaction for fast food outlets. International journal of quality & reliability management, Vol. 21 No. 5, pp. 545-63 34-50.
  5. Melachrinoudis, E., & Olafsson, M. (1995). A microcomputer cashier scheduling system for supermarket stores. International Journal of Physical Distribution & Logistics Management, 25(1).
  6. Mykoniatis, K., Shirzaei, S., Katsigiannis, M., Panagopoulos, A. A., Deb, S., Potter, T., & Angelopoulou, A. (2020). Society 5.0: A Simulation Study of Self Checkout Operations in a Grocery Store. 32nd European Modeling & Simulation Symposium.
  7. Stone, A., (2012). Why Waiting Is Torture. The New York Times. Retrieved on May 2, 2021 from:
  8. Tasar, B., Ventura, K., & Cicekli, U. G. (2020). A simulation model for managing customer waiting time in restaurants: scenarios and beyond. British Food Journal.
  9. Vieira, A. A. C., Dias, L. S., Pereira, G., & Oliveira, J. A. (2018). Assessing the performance of a restaurant through discrete simulation in Simio. Available at: