Graphical Spreadsheet Simulation of Queues

Abstract

Graphical representations of spreadsheet queueing simulations can be used to teach students about queues and queueing processes. A customer graph shows the experience of every individual customer in a queue, based on arrival time, start of service, end of service, and showing clearly the length of time in queue and service time for each individual customer. The cumulative effect is powerful, illustrating how one long service time (or short interarrival time) can cause delays for many succeeding customers. The server graph (a Gantt chart) shows the experience of each server, illustrating how customers stack up, and the nature of periods of idle time. The graphs are linked to a spreadsheet simulation and update instantly when the simulation is replicated. The graphs illustrate the complete evolution of a queue (which simulation animations cannot do) and help provide a holistic view of queues. They can be used to teach students about the nature of queues and support active learning where the students articulate for themselves the cause of queue behaviors. This paper shows how graphical representations of spreadsheet queueing simulations can be used to give students a richer understanding of queues, provide a deeper understanding of simulation, and to serve as a lead-in to teaching queueing theory results. This paper builds on previous work on spreadsheet queueing simulation (Grossman, 1999), with the relevant material summarized in sections 2-4. The contribution of this paper (sections 5-8) is the development and use of "live" simulation graphs to provide a rich visual means for understanding queues and simulation, and techniques for using these graphs to motivate students, enhance their learning, and stimulate their interest in simulation.The queueing simulation and their graphical representations were implemented in Microsoft Excel 97, and any specific instructions below refer to this software package.

Web-based Simulations for Teaching Queueing, Little's Law, and Inventory Management

“…Yet it has the disadvantage of being a black box to the students; they are given no feeling for why the system should perform as the numerical outputs suggest. Finally, as pointed out by Ingolfsson and Grossman (2002) steadystate analytical results cannot model transient situations.…”

“…Options for teaching queueing include 1) observing real systems, e.g., going to the local coffee shop or bank and watching customers arrive and queue, 2) using some simulation software, 3) using analytic queueing models. For this discussion we break option 2 into two categories: 2a) animated simulations, e.g., Arena or Extend, and 2b) spreadsheet simulations, e.g., Ingolfsson and Grossman (2002) and Ashley (2002). Option 3 can be broken into 3a) purely analytic formulas, and 3b) software that does the calculations for analytic models, i.e., spreadsheet add-ins such as Queueing Toolpak (Ingolfsson and Gallop, 2003) and QMacros (Groenevelt,2002).…”

“…Again, we found little publicly-available simulation software that is designed for teaching these topics, so we developed our own. Ingolfsson and Grossman (2002) point out that the "customer graph" in a spreadsheet queueing simulation can be used to motivate an informal derivation of Little's Law. Other authors have developed spreadsheet simulations for a more generic process under variability (Hill, 2002),'Goldratt's Game' to demonstrate the effects of statistical fluctuations and dependent events (Johnson and Drougas, 2002), and even a golf course (Tiger and Salzer, 2004).…”

Simulação de um Controle de Semáforos Utilizando Planilhas Eletrônicas: Uma Proposta para Fins Didáticos

“…Ingolfsson & Grossman (2002) apresentam o uso de planilhas eletrônicas em Excel com uso de macros para geração de gráfi co de Gantt para representação gráfi ca capaz de mostrar detalhadamente o comportamento da fi la em estudo. Strang, K. D. (2012) usa planilha eletrônica para avaliar defi nições de distribuições para modelos de fi las numa abordagem determinística.…”

Teaching Note—Fitting a Theoretical Model to a Real Queue

“…In this journal, Mandelbaum and Zeltyn (2010) have described the development of a service engineering course largely based on queues, which features extensive data analysis. Ingolfsson and Grossman (2002) used spreadsheet simulations and graphs to demonstrate emergent properties of queues, also based on real data. The principal contribution of this teaching note is to show how the simple assignment described here is set up to have a strong formative component (Wikipedia 2011).…”