1
ISyE 6644 — Summer 2025 — Projects!
(Revised 5/25/25)
Some Ground Rules:
• Pick one project that you find interesting. The projects are all intended to be a
little open-ended, but do not pick a project that will kill you time-wise!
• You are allowed to change your project later on as long as you run it by us first.
• You are allowed to work in groups that are reasonably sized, though you will have
to form the groups on your own. (Suggested group sizes are given in the text of
each problem.)
• The topics range from computer-intensive to more statistically oriented. When
computer work is necessary, you are allowed to use whatever computer languages
you’d like, e.g., R, Minitab, Matlab, Python, Excel, and (of course) computer-
simulation languages like Arena.
• In order to save time and effort and to avoid an overwhelming number of emails,
please do not ask us about minor problem assumptions — simply state the assump-
tions that you are using and proceed. If you find that you cannot understand a
problem unless you ask us several questions about the problem, then you should
instead choose a different problem!
• Start now! There will be no time at the end of the semester for extensions!
• Do not plagiarize! And don’t use ChatGPT to produce significant con-
tent! We have seen everything, and we will catch you!
• Good luck, and have fun!
Some Suggested Projects for ISyE 6644:
Applications-Oriented Problems
1. (1–2 group members) Digital Twins. Using modern tagging technology, it is possible
to obtain real-time snapshots of a manufacturing (or other) system that gives you
information about where everything is and what it’s currently doing. You can then
use this information to run a simulation to help with decision-making based on
almost-perfect current knowledge. Prepare a tutorial on this digital twin paradigm,
especially with respect to decision-making based on simulation. I’d really like you
to include a state-of-the-art reference list on current research and applications.
, 2
2. (2 members) Go to some intersections and model a couple of traffic lights. Collect
some real data. Try to answer as many interesting questions as you can think of. For
instance, what would the effect of synchronization be? Or, how do cell phones affect
driver behavior? Justify everything you conclude by conducting careful output
analysis. This could be a great project!
3. (1–2 members) Pandemic Flu Spread. Consider a classroom of 61 elementary school
kids. 60 of the kids are healthy (and susceptible to flu) on Day 1. Tommy (the
61st kid) walks in with the flu and starts interacting with his potential victims. To
keep things simple, let’s suppose that Tommy comes to school every day (whether
or not he’s sick) and will be infectious for 3 days. Thus, there are 3 chances for
Tommy to infect the other kids — Days 1, 2, and 3. Suppose that the probability
that he infects any individual susceptible kid on any of the three days is p = 0.01;
and suppose that all kids and days are independent (so that you have i.i.d. Bern(p)
trials). If a kid gets infected by Tommy, he will then become infectious for 3 days
as well, starting on the next day.
(a) What is the distribution of the number of kids that Tommy infects on Day 1?
(b) What is the expected number of kids that Tommy infects on Day 1?
(c) What is the expected number of kids that are infected by Day 2 (you can
count Tommy if you want)?
(d) Simulate the number of kids that are infected on Days 1,2,. Do this many
times. What are the (estimated) expected numbers of kids that are infected
by Day i, i = 1, 2, . . .? Produce a histogram detailing how long the “epidemic”
will last.
(e) What if each kid has a 50–50 chance of already being immunized (and the
immunization works perfectly)?
4. (1–2) members) Pandemic Flu Spread (differential equation version). Look up and
model in something like MATLAB a continuous-time SEIR (susceptible-exposed-
infectious-removed) pandemic flu spread model or one of its variants. This is a de-
terministic, differential equartions model that is nonetheless a simulation. I believe
that MATLAB and maybe even R have packages that will make this a reasonable
undertaking. I’d expect you to provide a tutotial, in addition to several examples,
and some general conclusions.
5. (2 members) Model, simulate, and analyze the operation of a fast food restau-
rant that includes a drive-thru. For example, most McDonald’s, Chick-fil-A, etc.
would be fine. At the very least, include some analysis of the arrival and service
ISyE 6644 — Summer 2025 — Projects!
(Revised 5/25/25)
Some Ground Rules:
• Pick one project that you find interesting. The projects are all intended to be a
little open-ended, but do not pick a project that will kill you time-wise!
• You are allowed to change your project later on as long as you run it by us first.
• You are allowed to work in groups that are reasonably sized, though you will have
to form the groups on your own. (Suggested group sizes are given in the text of
each problem.)
• The topics range from computer-intensive to more statistically oriented. When
computer work is necessary, you are allowed to use whatever computer languages
you’d like, e.g., R, Minitab, Matlab, Python, Excel, and (of course) computer-
simulation languages like Arena.
• In order to save time and effort and to avoid an overwhelming number of emails,
please do not ask us about minor problem assumptions — simply state the assump-
tions that you are using and proceed. If you find that you cannot understand a
problem unless you ask us several questions about the problem, then you should
instead choose a different problem!
• Start now! There will be no time at the end of the semester for extensions!
• Do not plagiarize! And don’t use ChatGPT to produce significant con-
tent! We have seen everything, and we will catch you!
• Good luck, and have fun!
Some Suggested Projects for ISyE 6644:
Applications-Oriented Problems
1. (1–2 group members) Digital Twins. Using modern tagging technology, it is possible
to obtain real-time snapshots of a manufacturing (or other) system that gives you
information about where everything is and what it’s currently doing. You can then
use this information to run a simulation to help with decision-making based on
almost-perfect current knowledge. Prepare a tutorial on this digital twin paradigm,
especially with respect to decision-making based on simulation. I’d really like you
to include a state-of-the-art reference list on current research and applications.
, 2
2. (2 members) Go to some intersections and model a couple of traffic lights. Collect
some real data. Try to answer as many interesting questions as you can think of. For
instance, what would the effect of synchronization be? Or, how do cell phones affect
driver behavior? Justify everything you conclude by conducting careful output
analysis. This could be a great project!
3. (1–2 members) Pandemic Flu Spread. Consider a classroom of 61 elementary school
kids. 60 of the kids are healthy (and susceptible to flu) on Day 1. Tommy (the
61st kid) walks in with the flu and starts interacting with his potential victims. To
keep things simple, let’s suppose that Tommy comes to school every day (whether
or not he’s sick) and will be infectious for 3 days. Thus, there are 3 chances for
Tommy to infect the other kids — Days 1, 2, and 3. Suppose that the probability
that he infects any individual susceptible kid on any of the three days is p = 0.01;
and suppose that all kids and days are independent (so that you have i.i.d. Bern(p)
trials). If a kid gets infected by Tommy, he will then become infectious for 3 days
as well, starting on the next day.
(a) What is the distribution of the number of kids that Tommy infects on Day 1?
(b) What is the expected number of kids that Tommy infects on Day 1?
(c) What is the expected number of kids that are infected by Day 2 (you can
count Tommy if you want)?
(d) Simulate the number of kids that are infected on Days 1,2,. Do this many
times. What are the (estimated) expected numbers of kids that are infected
by Day i, i = 1, 2, . . .? Produce a histogram detailing how long the “epidemic”
will last.
(e) What if each kid has a 50–50 chance of already being immunized (and the
immunization works perfectly)?
4. (1–2) members) Pandemic Flu Spread (differential equation version). Look up and
model in something like MATLAB a continuous-time SEIR (susceptible-exposed-
infectious-removed) pandemic flu spread model or one of its variants. This is a de-
terministic, differential equartions model that is nonetheless a simulation. I believe
that MATLAB and maybe even R have packages that will make this a reasonable
undertaking. I’d expect you to provide a tutotial, in addition to several examples,
and some general conclusions.
5. (2 members) Model, simulate, and analyze the operation of a fast food restau-
rant that includes a drive-thru. For example, most McDonald’s, Chick-fil-A, etc.
would be fine. At the very least, include some analysis of the arrival and service
