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I teach a discrete-event system simulation course in Fall 2020. As with most DES simulation courses, students have term projects that involve gathering real-world data and building stochastic input models that they can use to do a simulation study of the system.

In the past, students would frequently choose to study the operations of local restaurants (for example) or traffic intersections, primarily because the data was easy to gather. This fall, due to COVID-19, I am uncomfortable asking them to do this. Furthermore, some students may be attending from remote, and the local data sources may not be as rich as they usually are.

So I am looking for alternatives. For example, I have considered some of the many repositories of webcam's on the Internet that might be observed. I would like to avoid generating synthetic data; I would especially like to avoid students generating synthetic data (and then having to do input models of the data they just generated). There are simulation competitions (such as IISE/Arena), but I do not think it is feasible to have the whole class work on the same competition/competitions (and last year's IISE/Arena competition provided input models for the students, which meant that students choosing that experience were able to skip a major component of simulation modeling).

Does anyone here have any suggestions for real-world simulation activities appropriate for term projects for small groups of students who might be attending class virtually? Again, the goal is to not ask them to subject themselves to additional exposure risk just to complete the project.

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  • $\begingroup$ What is the level of technological knowledge and general background of the students? $\endgroup$ – dhasson Jun 27 at 0:52
  • $\begingroup$ Can they model PPE or testing supply chains and operations? And to make it more interesting and valuable, have them try to optimize ("simulation optimization"), or at least improve supply chains and operations. That would be real O.R. $\endgroup$ – Mark L. Stone Jun 27 at 1:11
  • $\begingroup$ @dhasson: This is a 400-level course required for Industrial Engineering majors, focusing on implementation and statistical analysis of discrete event system simulation models. They come into the class with basic background in programming, probability, statistical inference (t-tests, ANOVAs, and linear regression). Most have taken a stochastic OR course, and many have had a course on quality or reliability. $\endgroup$ – Ted Jun 28 at 1:17
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    $\begingroup$ @Mark: I'm sure that some of these students will come up with similar project ideas. My system dynamics modeling students in the spring had a bunch of COVID-related models (including toilet paper supply chains). The problem for the DES course is that they usually need fine-grained data sets on which they can do stochastic input modeling. Traditionally, students learn the complications of gathering and working with this data by taking it themselves. I don't want to ask them to do that this fall though. $\endgroup$ – Ted Jun 28 at 1:26
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Someone recently pointed me to a journal article about the movement of shoppers in a supermarket. A point of interest is that markets apparently use RFID technology to track shopper movements. If you could get a market (or market chain) to provide you with anonymized movement data and maybe store layouts, you might be able to have the students simulate something related to shoppers. I'm particularly curious whether the one-way lanes instituted in stores actually reduce COVID transmission (because you are less likely to pass someone face to face), increase it (because obeying the rules means rolling the cart over extra distances to get to the end of an aisle where you are allowed to enter) or neither.

An episode of the INFORMS Resounding Human podcast dealt with using simulation models to help hospitals develop policies for diverting/reassigning beds and personnel when something happens (such as a cluster of COVID patients needing care). I suspect that you could get information on department sizes, bed counts and ballpark arrival rates either from some local hospital or from an academic who studies hospital management. The students could then experiment with "shocks" to the system where either you or they could arbitrarily pick parameter values within reason. For instance, what is a good response to an increase of 2 COVID patients per day, or an increase of 10 per day, or an outbreak of the seasonal flu, or a mass casualty event?

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  • $\begingroup$ That reminds me of a discussion I had with the great probabilist, J. Michael Steele www-stat.wharton.upenn.edu/~steele, from whom I had taken a theoretical probability sequence, and who was in the Statistics Department at the time, about the value of O.R. He said that out of all of queueing theory, you could boil its useful contribution down to (and I remember this word for word): "When the line gets back to the peanut butter, open up another register." $\endgroup$ – Mark L. Stone Jun 28 at 1:59
  • $\begingroup$ Some other quotes in the theoretical probability course (as opposed to one on one discussion relayed above): "Roll your own maximal inequality". And I remember well, when just starting an elaborate proof of the overall behavior of some stochastic process which was well-behaved on a diagonal sequence, a then student, now well-known former chairman of the Stanford Statistics Department, asked why there was anything to prove given how well-behaved the stochastic process was. Steele's response "it could be a real Mother on the rest of the space".. $\endgroup$ – Mark L. Stone Jun 28 at 2:19
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Many real-world datasets can be found using the google search engine dedicated to the dataset search in this web address. For example, you can use the datasets about the airports instead of restaurants, or you can search for 'Simulation Data' to find interesting datasets ready to be used in a simulation project.

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