Punk Rock Operations Research

View Details

I have the pleasure of giving a keynote talk at the INFORMS Security Conference on July 30, 2024. My keynote talk was entitled, “Smarter Decisions for a Secure World: A Roadmap for Operations Research.” Below I provide an outline of my talk and the publications I referenced in my talk.

Talk outline:

Advancing OR Through Security Challenges:
- Overcoming difficult security obstacles has sparked innovations that propel OR forward.
Elevating OR to New Heights:
- Addressing existing security and resilience challenges will lead OR to greater achievements.
Nurturing the OR Ecosystem:
- Merely doing OR isn’t sufficient; we must actively cultivate the OR ecosystem.

References:

Florence N. Trefethen (1954). “A History of Operations Research,” in Joseph F. McCloskey and Florence N. Trefethen (eds.), Operations Research for Management, Baltimore: Johns Hopkins University Press, pp. 3-35.
Articles and resources about the origins of operations research: https://www.informs.org/Explore/History-of-O.R.-Excellence/Bibliographies/The-Origins-of-OR
P.M. Morse (1952). Operations research – what is it? Journal of Applied Physics 23(2), 165-172. https://doi.org/10.1063/1.1702167
Hall Jr, J. R., & Hess, S. W. (1978). OR/MS: Dead or dying? RX for survival. Interfaces, 8(3), 42-44. https://doi.org/10.1287/inte.8.3.42
Ackoff, R. L. (1979). The future of operational research is past. Journal of the operational research Society, 30(2), 93-104. https://doi.org/10.1057/jors.1979.22
INFORMS (1994). Case Western Reserve University (Case Institute of Technology), Available at: https://www.informs.org/Explore/History-of-O.R.-Excellence/Academic-Institutions/Case-Western-Reserve-University-Case-Institute-of-Technology (Accessed in July 2024)
Green, L.V. & Kolesar, P.J. (2004). Improving emergency responsiveness with Management Science.” Management Science, 50(8), 1001-1014. https://doi.org/10.1287/mnsc.1040.0253
Budiansky S. (2013) Blackett’s War: The Men Who Defeated the Nazi U-Boats and Brought Science to the Art of Warfare. Alfred A. Knopf Inc.: New York.
Larson, R.C., Metzger, M.D., and Cahn, M.F. (2006) Responding to emergencies: Lessons learned and the need for analysis, Interfaces 36(6), 486-501. https://doi.org/10.1287/inte.1060.0250
Wein, L.M. (2009). Homeland security: from mathematical models to policy implementation: The 2008 Philip McCord Morse Lecture, Operations Research 57(4), 801-811. https://doi.org/10.1287/opre.1090.0695
J. Birge (2022). George Bernard Dantzig. Production and Operations Management 31(5), https://doi.org/10.1111/poms.13751

My publications referenced in the talk:

Albert, L.A., Nikolaev, A., and Jacobson, S.H. (2023). Homeland Security Research Opportunities. IISE Transactions 55(1), 22-31. DOI: 10.1080/24725854.2022.2045392
Albert, L.A., Nikolaev, A., Lee, A.J., Fletcher, K., and Jacobson, S.H., (2021). A Review of Risk-Based Security and Its Impact on TSA PreCheck, IISE Transactions 53(6), 657 – 670. https://doi.org/10.1080/24725854.2020.1825881
Enayaty-Ahangar, F., Albert, L.A., DuBois, E. (2020). A survey of optimization models and methods for cyberinfrastructure security. IISE Transactions 53(2), 182 – 198. https://doi.org/10.1080/24725854.2020.1781306
Schmidt, A.P. and L. A. Albert (2021). Designing pandemic-resilient voting systems. Socio-economic Planning Sciences, https://doi.org/10.1016/j.seps.2021.101174
Schmidt, A.P. and Albert, L.A. 2024. Locating ballot drop boxes. IISE Transactions 56(4), 424 – 436. https://doi.org/10.1080/24725854.2023.2213754
Schmidt, A.P., Buell, D., and Albert, L.A. 2024. Optimal consolidation of polling locations. To appear in Manufacturing & Service Operations Management. https://doi.org/10.1287/msom.2022.0497
Zheng, K., Albert, L., Luedtke, J.R., Towle, E. 2019. A budgeted maximum multiple coverage model for cybersecurity planning and management, IISE Transactions 51(12), 1303-1317.
Zheng, K., and Albert, L.A. 2019. Interdiction models for delaying adversarial attacks against critical information technology infrastructure. Naval Research Logistics 66(5), 411 – 429.
V.M. White, S.A. Avendano, L.A. Albert, A.E. Zgierska, J. Balles, G. Zayas–Cabán. 2021. Impact of a community-policing initiative promoting substance use disorder treatment over criminal charges on arrest recidivism, Drug and Alcohol Dependence 227(1), 108915.
Nyland, J.E., Zhang, A., Balles, J. A., Nguyen, T.H., White, V., Albert, L.A., Henningfield, M.F., Zgierska, A.E. 2024. Law enforcement-led, pre-arrest diversion-to-treatment may reduce crime recidivism, incarceration, and overdose deaths: Program evaluation outcomes. To appear in Journal of Substance Abuse Treatment. Preprint available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4682322
White, V.M., and Albert, L.A. 2023. Evaluating diversion and treatment policies for opioid use disorder, Under review, University of Wisconsin-Madison. Preprint available at: https://arxiv.org/abs/2311.05076.
Albert, L. America’s data illiteracy imperils its worldwide lead in artificial intelligence. The Hill, June 23, 2023.
Gerstmann, E. and Albert, L. (2024). America is facing a STEM and data education crisis, Op-Ed in The Hill, February 3, 2024.

View Details

I visited Stockholm this summer after the EURO Conference. While in Stockholm, I visited the Nobel Prize Museum to celebrate the achievements of the laureates, including the operations research Nobel laureates. The Nobel Prize Museum displays items from many of the laureates. I was delighted to see Alvin Roth’s “Mr. Matching” T-shirt in the exhibit. Al Roth and Lloyd Shapley were awarded the 2012 Nobel Prize in economics for “the theory of stable allocations and the practice of market design.”

How to bring different players together in the best possible way is a key economic problem. Lloyd Shapley studied different matching methods theoretically and, beginning in the 1980s, Alvin Roth used Shapley’s theoretical results to explain how markets function in practice. Through empirical studies and lab experiments, Roth demonstrated that stability was critical to successful matching methods. Roth has also developed systems for matching doctors with hospitals, school children with schools, and organ donors with patients. [From NobelPrize.org]

You can read more about Al Roth’s prize here and Lloyd Shapley’s prize here.

You can also read about Al Roth’s research in a book he wrote entitled Who gets what–and why: The new economics of matchmaking and market design. This interesting book makes matching markets accessible, and I highly recommend it.

“Alvin Roth’s “Mr. Matching” T-shirt at the Nobel Prize Museum

View Details

At the EURO Conference in Copenhagen in July 2024, I was honored to present a talk entitled “Tackling hard problems: On the evolution of operations research” in the “Moments in the history or OR” stream organized by Roberto Rossi and Gerhard-Wilhelm Weber. I was delighted to give this talk, which I organized around several of the articles I wrote in ORMS Today and on this blog during my term as INFORMS President in 2023. These articles are listed at the end of this post along with a list of the sources I drew upon. I am also sharing my slides.

My articles 1. L. Albert (2020). Firsts in operations research. Punk Rock Operations Research blog post, Available at: https://punkrockor.com/2020/02/17/firsts-in-operations-research/ 2. L. Albert (2022). Operations research was declared dead in 1979. Punk Rock Operations Research blog post, Available at: https://punkrockor.com/2022/04/07/operations-research-was-declared-dead-in-1979/ 3. L. Albert (2023a). 10 facts about the origin of operations research. ORMS Today, Available at: https://pubsonline.informs.org/do/10.1287/orms.2023.03.04/full 4. L. Albert (2023b). On George Dantzig, Good Will Hunting, and Tackling Hard Problems. Punk Rock Operations Research blog post, Available at: https://punkrockor.com/2023/06/05/on-george-dantzig-good-will-hunting-and-tackling-hard-problems/ 5. L. Albert (2023c). Operations Research: What is it?. Punk Rock Operations Research blog post, Available at: https://punkrockor.com/2023/07/31/operations-research-what-is-it/ 6. L. Albert (2023d). So your mother wanted you to be a doctor, but a PhD in OR? Post on LinkedIn. Available at: https://www.linkedin.com/feed/update/urn:li:activity:7132404427998597120/

References1. Florence N. Trefethen (1954). “A History of Operations Research,” in Joseph F. McCloskey and Florence N. Trefethen (eds.), Operations Research for Management, Baltimore: Johns Hopkins University Press, pp. 3-35. 2. Budiansky, S. (2013). Blackett’s War: The Men Who Defeated the Nazi U-Boats and Brought Science to the Art of Warfare Warfare. Vintage. 3. INFORMS. Articles and resources about the origins of operations research: https://www.informs.org/Explore/History-of-O.R.-Excellence/Bibliographies/The-Origins-of-OR 4. P.M. Morse (1952). Operations research – what is it? Journal of Applied Physics 23(2), 165-172. https://doi.org/10.1063/1.1702167 5. Hall Jr, J. R., & Hess, S. W. (1978). OR/MS: Dead or dying? RX for survival. Interfaces, 8(3), 42-44. https://doi.org/10.1287/inte.8.3.42 6. Ackoff, R. L. (1979). The future of operational research is past. Journal of the operational research society, 30(2), 93-104. https://doi.org/10.2307/3009290 7. Herbert Halbrecht, (1972). So your mother wanted you to be a doctor, but a PhD in OR? Interfaces, 2(2), pp. 44-49. https://www.jstor.org/stable/25058872

View Details

Sometimes I receive a message or thank you note that truly makes my day. You know the ones—they’re the ones that make you realize that you made a difference to somebody. When I receive one of these notes, I get a little teary eyed, print it, and save it in a box in my office. One day when I retire, I’m going to take the box of meaningful notes and leave the rest behind.

View Details

The two point conversion has become more popular in National Football League (NFL) games, and it has become a popular topic of conversation in the NFL playoffs leading up to the Super Bowl. I once wrote a blog post that uses dynamic programming to identify when to go for 2 based on the score differential and the number of possessions remaining in the game. The analysis also shows what difference the choice makes, noting that most of the time the win probability does not make a huge difference in the outcome of the game, affecting the win probability by less than one-percent in most cases. In this post, I delve into the two point conversion, covering rule changes, football strategy, and assumptions.

By the numbers

In 2023, a typical NFL team attempted a two-point conversion about once 1 every 4 games and was successful just over half the time. A decade ago, a typical team attempted a two-point conversion about once 1 every 8 games and was successful just under half the time. Two point conversions became more popular and more successful. Two rule changes influenced these changes:

In 2015, the NFL moved the extra point attempt from the 2 yard line to the 15 yard line.
- The proportion of extra points that succeeded lowered from 0.996 (in 2015) to 0.941 in the seasons after the change. A chart in an article on Axios illustrates how dramatic this change has been on extra point success rates.
In 2023, a new rule allowed offenses to attempt a two point conversion from the 1 yard line (instead of the 2 yard line) when there was a defensive penalty on a touchdown.
- The proportion of two point conversions that succeeded increased from about 0.5 to 0.565, the first season the success rate was well-above 0.5.

The difference of one yard makes a difference. For comparison, attempts to go for it on fourth down and two yards to go succeed 57.2% of the time, and this increases to 65.5% for fourth down and one yard to go.

Decision-making

After a team scores a touchdown, they have essentially two choices. They can kick an extra point or they can attempt a two point conversion. The proportion of extra point attempts that were successful in 2023 was 0.96, and historically the proportion of two-point conversions that have been successful is 0.48. Therefore, on average, the extra point attempt or two-point conversion have promised roughly the same number of points on average.

The goal is not to maximize expected points, it’s to win the game. The two rule changes above have tipped decision-making in favor of the two point conversion in more situations by making the extra point attempt less attractive and the two point conversion more attractive.

The “best” choice for improving the chance of winning is situational and depends on a few factors:

Point differential
Time remaining (including time outs remaining)
Strategies that each team may employ in the resulting situations
Specific teams and match-ups

The dynamic programming model takes the first two factors into account, where the time remaining is modeled as the number of possessions remaining. Dynamic programming is an algorithmic approach that essentially enumerates the possible outcomes of the remaining drives in the game to quantitively determine the best options for the average team. This approach does not take specific situations into consideration, however, it is informative as a baseline.

Using 2023 data, I present a chart of when the average team should attempt a two-point conversion based on the 2023 data. In this chart, pictured below, the rows capture the point differential when a touchdown is scored, with a negative score capturing how many points a team is behind. The columns capture how many possessions are remaining in the game, including the current possession. Therefore, as the game evolves, we move left in the table. The team with the final possession of the game has 1 possession remaining in the table, and a team with two possessions left will not get the ball back. Note that there are 22.2 total possessions per game, on average, so the last 6 possessions or so capture the fourth quarter.

Table 1: when an average team should choose to go for a two point conversion after scoring a touchdown based on the score differential and number of remaining possessions [2023 data] According to this chart, an average team should attempt a two point conversion in many situations, including when a touchdown in the fourth quarter puts the team down by 8, 5, 2, or 1 or up by 1, 2, 4, 5, and 7. A team should not go for two when a touchdown puts the team down by 4 or 3, puts the team up by 3 or 6, or ties the game.

Compared to 2014–before the two rule changes mentioned above–two point conversations are now the better choice in more situations. For example, a two point conversation now is the better choice for the average team when a touchdown in the fourth quarter puts the team down by 1.

My analysis, as Prof. Ben Recht notes in an outstanding post on two point conversions, makes a number of assumptions. While some assumptions are more reasonable than others, the model still offers important insights that are not obvious before crunching the numbers.

A better way to decide whether to attempt a two point conversion

When I listen to broadcasts, I get frustrated with the analytics discourse from the commentators, which is often some version of “The analytics tell you to go for 2 in this situation.”

This is wrong. Analytics do not tell people what to do. Analytics are a collection of tools that can inform decision-making, with people making the final decisions.

If I were a football coach, I would not use the chart above. I would ask for a different chart based on the same analysis. Below, I create this chart.

No team is the average team. As noted earlier, the analysis using dynamic programming makes some assumptions that are not totally valid, including that an average team is facing an average team. The chart above always gives the same answer for the same point differential and possessions remaining, and it does not reflect other attributes of the situation at hand.

One specific situation that may affect the decision is the play that a team has available for the two point conversion. For example, historically 43.4% of pass plays have succeeded, whereas 61.7% of run plays have succeeded. Having a play in mind–and its associated likelihood of success–should affect the decision. Another situation is the team’s opponent, including their run and pass defense.

There are two ways to make the dynamic programming more informative for specific situations:

Change the inputs to reflect the current match-up. In this case, one could change the probability that a two point conversion would be successful, the probability that an extra point is successful, the probability that a drive ends in a touchdown, and the probability that a drive ends in a field goal.
Instead of only reporting the best decision (go for 1 or go for 2), the analysis can be used to report the probability that a two point conversion should be successful for it to be the better choice than attempting an extra point. In this case, a decision-maker (a football coach) can estimate how likely their play would success against the team they are playing in the specific situation they are facing.

I illustrate the second approach below using the dynamic programming analysis above. Instead of reported the binary decision of going for 1 or 2 as before, I report the two point conversion probability of success above which going for two is the better decision. Again, I use data based on average teams. The lower the probability in the chart, the more attractive the two point conversion is.

Some decisions are clear cut. A 0.00 indicates that a team should always go for a two point conversion, and a 0.95 indicates that a team should essentially always attempt the extra point. Most of the probabilities are in between, which means that the “best” decision is not clear cut in most cases.

Table 2: the minimum probability of success associated with a two point conversion above which going for 2 is the better decision based on the score differential and number of remaining possessions. Situations that always result in a loss or a win are labeled “Lose” and “Win,” respectively [2023 data]This new chart is more nuanced than the first chart in this post.

Sometimes it is obvious to go for 2. A two point conversion is the better decision with a play that has a mere 25% probability of success when a touchdown in the fourth quarter puts the team down by 10, 5, or 2, or up by 1 or 5.
Sometimes it is obvious to attempt an extra point. Going for two is the better decision with a play with a very high, 75% probability of success, which occurs when a touchdown puts a team down 7 or 3, up 3 or 8, or ties the game. Very few plays can expect a 75% probability of success, so in these situations it almost always is better to attempt the extra point.

Now consider strategies for two different teams:

Team A with a two point conversion play with a 40% probability of success, and
Team B with a two point conversion play with a 60% probability of success.

Team A and Team B would make different decisions if a touchdown in the fourth quarter puts them down by 9, 6, 4 or up by 3, 6, or 7.

Another insight: Both Team A and Team B should both attempt a two point conversion if a touchdown puts them down by 8.

Therefore, the same chart yields different “best” solutions for different teams based on the situations at hand. This insight follows directly from the numbers and the modeling, however, it is almost always overlooked in discussions on football analytics.

Related articles and posts:

When to go for a two point conversion instead of an extra point: a dynamic programming approach (Punk Rock Operations Research)
The rise of the two point conversion from The Upshot at the New York Times
When to go for 2, for real from FiveThirtyEight
Should you go for 2 when down 8? An analysis by Ben Recht
Should a football team run or pass? A game theory and linear programming approach (Punk Rock Operations Research)

View Details

It was an honor to serve as the President of INFORMS in 2023. During my term, I wrote a president’s column in ORMS Today entitled “Presidential Punk Rock OR.” You can read all of my columns here.

In my last president’s column, I retrospectively summarized my term by the numbers. I’ve reprinted my final column below:

As I write my last “Presidential Punk Rock O.R.” column, I am officially the INFORMS past-president. Now that my term has ended, I have been reflecting on my time as the 2023 INFORMS president, and will summarize my year by the numbers. In 2023, I …

Chaired 4 Board of Directors meetings held over 9 days

Worked with 19 board members (as president and president-elect)

Wrote 4 OR/MS Today print columns

Including this article, published an additional 9 Presidential Punk Rock O.R. online articles and videos

Recorded 7 Resoundingly Human podcasts

Published 2 op-eds (in the Chicago Tribune and The Hill)

Moderated 1 panel discussion (at the Conference of International Federation of Operational Research Societies (IFORS))

Participated in 8 briefings with U.S. Senate, House and White House staffers

Chaired 12 INFORMS Executive Committee meetings

Attended 2 INFORMS Book Club meetings (and read 5 of the selected books throughout the year)

Recorded 1 data literacy webinar for policymakers

Announced 1 Franz Edelman Award winner

Attended 20 award ceremonies, receptions and meals (12 at the INFORMS Annual Meeting and 8 at the Analytics Conference)

Wrote 30 INFORMS Connect posts as well as many more posts on LinkedIn and X

Showed up in approximately 1 gazillion pictures with INFORMS award winners at INFORMS conferences

Most importantly, met countless members (Although I tried to meet every single member, I did not achieve that goal. Please introduce yourself in 2024 if we have not yet met.)

It has truly been an honor to serve as the 2023 INFORMS president. I look forward to continuing volunteer service to INFORMS and the OR/MS community as the past-president in 2024, and beyond as an INFORMS member. I know 2023 will be hard to beat, but I will keep crunching the numbers and the countless ways INFORMS members are making smarter decisions for a better world.

From ORMS Today

I’m grateful for the countless ways INFORMS members are making smarter decisions for a better world!

View Details

It’s a new year, and I’m reflecting on 2023 and looking forward to 2024. New Years resolutions. As usual, I have set New Year’s resolutions for the coming year. I will continue to focus on self-care and wellness in the coming year. My goals for the year are to continue four habits that I set this past year as well as three new resolutions.

2023 self-assessment. You can review my seven resolutions for 2023 here. In my self-assessment, I did well with physical therapy, public outreach, meditation, and eating leafy green vegetables. I started practicing the piano in the spring and summer and have been on hiatus since then. I hope to return to the piano in 2024. I did not make as much time for writing as I would have liked last year, nor did I master the art of delegation. I hope to do better with both in 2024. Many readers of this blog asked me about how I was doing with leafy greens this past year, and it motivated me to stick with the habit.

Life has many unexpected turns. I am proud two report that I successfully completed two resolutions in 2023 that I never set to begin with. In March, I started a sourdough starter and learned how to bake sourdough (my favorite is an oat and flax loaf), and I’m proud to say that my sourdough starter is still alive. I also joined the INFORMS book club as well as a book club with friends. As a result, I made more time to read for fun than I have in years, although I generally “read” the audiobook versions of the selections to fit reading in my schedule.

My New Year’s resolutions for 2024 are:

Sleep at least 8 hours per night (at least 5 nights per week).
Read more for fun.
Continue to eat leafy greens.
Write a proposal, a teaching case study, and an op-ed.
Continue to meditate daily and adjust my practice as needed.
Do physical therapy and/or yoga (at least 3 days/week).
Do something every week that scares me.

What are your resolutions? I asked this on X and received a few answers. Answer in a comment below or in X in response to my tweet.

View Details

“Operations research – what is it?” is the title of a paper by Philip McCord Morse published in the Journal of Applied Physics in 1952. The paper is a transcript of a lecture Morse gave at the conference on Applications of Operations Research in Industry at Case Institute of Technology, Cleveland, Ohio, November 8-10, 1951. […]

View Details

The 23rd Conference of the International Federation of Operational Research Societies (IFORS) was held in Santiago, Chile on July 10-14, 2023. I attended and enjoyed the conference talks and conversations. I appreciate the efforts of the organizing and program committees, especially co-chairs Jorge Vera and Rafael Epstein as well as program chair Alice Smith. Here […]

View Details

The documentary series “Muscles & Mayhem: An Unauthorized Story of American Gladiators,” which was released by Netflix this month, has reminded me of the television reality show American Gladiators that debuted in 1989. The television show featured amateur athletes who participated in various strength and agility challenges in competition against each other and the show’s […]

View Details

George Dantzig invented the simplex algorithm and contributed to linear programming. He introduced the world to the power of optimization, which has led to massive increases in productivity and drives the global economy (Read more in Prof. John Birge’s article here).

The movie “Good Will Hunting” has a scene that is inspired by the life of George Dantzig. In the movie, Matt Damon plays an MIT janitor who anonymously solves a difficult math problem that a math professor posted on a hallway blackboard.

In real life, George Dantzig once arrived to Jerzy Neyman’s class late while he was a graduate student at the University of California-Berkeley. He wrote down what be believed were two homework problems posted on the blackboard, not knowing that the problems were unsolved math problems, because he had missed the announcement at the beginning of class. he then solved the problems, apologizing to Prof. Neyman that it took so longer to do the homework. They later became the foundation of his thesis. Read more here.

“If I had known that the problems were not homework but were in fact two famous unsolved problems in statistics, I probably would not have thought positively, would have become discouraged, and would never have solved them,”

George Dantzig

I like this story. I also like Good Will Hunting and recommend it without hesitation.

I reflected on this story after returning from the 2023 INFORMS Analytics Conference.

I have always been impressed by how the operations research community has never shied away from hard problems in theory, computation or practice. The operations research community has been tackling hard problems since its early days during World War II, prior to George Dantzig’s solutions to the (then) unsolved problems in statistics.

We are still at it.

Our dedication to solving hard problems is evident at the Edelman Gala at the INFORMS Analytics Meeting, from which I recently returned (watch this year’s gala here). The Edelman Gala celebrates achievements in operations research and analytics, and it awards the Franz Edelman Award and the Daniel H. Wagner Prize. These prizes recognize the application and implementation of solutions that have made a big difference. The finalists of these awards embody the spirit of George Dantzig, and they reinforce that we solve problems and make a real difference in the world.

View Details

A gaggle of geese.

A murder of crows.

A parliament of owls.

A flamboyance of flamingos.

A pride of lions.

What do you call a group of operations researchers?

I asked this question to the OR community on the INFORMS Open Forum. Here are some of the answers I received:

A tableau of optimizers (from Ralph Asher)
A distribution of problem solvers (from Anthony Bonifonte)
A model of operations researchers (David Tullet)
A process of industrial engineers
A sequence of analysts (from Kara Tucker)
A quantity of quants (from Paul Rubin)
A queue of operations researchers (from Greg Godfrey)
A simplex of operations researchers (from Tallys Yunes)

What is your answer?

View Details

In my last lab meeting with the five PhD students in my lab, we discussed how to collaborate on research. While I have a lab compact conveying my expectations for myself and students who work under my supervision, the lab compact focuses more on individual expectations rather than collaboration. I decided to give collaboration more attention.

As a group, we collaboratively edited a document in real-time that outlines techniques that various lab members have found to be effective in their collaborations. Most of their collaborations are with me, their advisor, and sometimes a co-advisor. Several items on the list sparked deeper discussions, which we will explore in more detail in further lab meetings. Here is our preliminary list of how to collaborate on academic research:

Write papers as you research (not all at the end)
- There are many different ways to do this, so this topic would benefit from further discussion.
- Structure the results section of your papers around key figures that tell the story. Restructure the earlier sections of the paper as necessary
Document research as you research (and share with collaborators at meetings)
- Create PowerPoint presentations as you do research to stay organized, summarize progress, share weekly progress, track milestones, and document main results
- Create text files after each meeting to summarize discussion and next steps
- Keep a lab notebook
- Write down what you complete every day so you can track your own progress.
Learn how to create figures to communicate research concepts and models to others (This is hard)
- When you see research talks, notice good figures and emulate them
Share files for collaborative writing
- Overleaf
- OneDrive
- Zotero – created shared set of papers (make corrections to BibTeX entries)
- Version Control – Github /Github Desktop
Task Management / tracking project progress
- Trello boards / Todoist boards / Notion / Obsidian
File management. Create a folder for each paper.
- We will dig into this in a future lab meeting

View Details

I spend a lot of my time thinking about the future in terms of engineering grand challenges, engineering education, and the impact that engineering can have on the world. I recently came across a 25+ year old quote about technological change that caught my attention.

“In the year 1500, after the printing press was invented, you did not have old Europe plus the printing press. You had a different Europe. After television, America was not America plus television. Television gave a new coloration to every political campaign, to every home, to every school, to every church, to every industry, and so on.

That is why we must be cautious about technological innovation. The consequences of technological change are always vast, often unpredictable and largely irreversible.”

Neil Postman, lecture at the Arts Center in Denver Colorado in 1997 entitled “Five Things We Need to Know About Technological Change“

Technological change being ecological is one of five ideas that Neil Postman outlined in his lecture. All five ideas are:

We always pay a price for technology.
There are always winners and losers.
The technology has a philosophy (epistemological, political or social prejudice). Sometimes this bias is to our advantage, and sometimes not.
Technological change is not additive; it is ecological.
Technology tends to control more of our lives than is good for us.

The entire lecture is interesting and relevant to the various forms of technological change we have experienced since he delivered the lecture in 1997. His lecture highlights the tremendous scope of impact that enablers of technological change have on our way of living.

Technological change is often at the hands of engineers. Recognizing this motivates engineering education to empower engineering students to be able to understand and influence the ecological changes that result from technological change for the better. This lecture will guide my thinking in this area in the future.

What do you think? Are these five ideas regarding technological change still true? How would you modify or add to the list?

View Details

I recently had a conversation with a graduate from of my department who has had a highly successful career in industry for the last 25 years since earning a Bachelors degree in Industrial Engineering at the University of Wisconsin-Madison. The conversation turned toward the value of an industrial engineering degree. The value, he argued, was in educating students about the decision sciences. This captures data driven decision-making, communication, and the human side of decisions, including emotions and cognitive biases:

“Industrial engineering is ultimately about how to make decisions and how to make them well. And that’s something that every organization values.”

While there are several other valuable skills one can learn in an industrial engineering program in addition to the decision sciences, this claim resonates with me. Industrial engineers don’t make things, we make decisions, and it’s hard to overstate how valuable and interesting this is.

What aspects of industrial engineering have been most valuable to you?

View Details

In preparation of the Super Bowl tomorrow, I have a roundup of sports analytics blog posts from Punk Rock Operations Research for further reading:

Why the New England Patriot’s decision to let the New York Giants score a touchdown in the 2012 Super Bowl made sense [Link]
The Green Bay Packers should have gone for it on fourth down: my analysis using decision trees [Link]
Before Sabermetrics there was football analytics. The first paper on football analytics was published in Operations Research in 1979 and was written by National Football League player Virgil Carter [Link]
When should a football team attempt a two point conversion after a touchdown? A dynamic programming approach [Link]
Should a football team run or pass? How to choose the mix of offensive plays to run using game theory and linear programming [Link]

Podcasts

A recent episode of Resoundingly Human (the INFORMS podcast) features a sports analytics discussion with Walt DeGrange [Link]

View Details

It’s a new year, and I’m reflecting on 2022 and looking forward to 2023. Today is my first day as INFORMS President, and that will be a major responsibility in the coming year. I’m excited and ready for the challenge.

I made a list of resolutions for 2023.

New Year’s resolutions in 2023

Do physical therapy every morning.
Improve my ability to delegate and manage situations when others delegate up.
Take advantage of public outreach opportunities in new formats for me.
Write and edit my writing every day, even if only for a few minutes.
Eat more leafy green vegetables.
Take up a musical hobby. I have been taking Irish dance lessons on zoom since the pandemic, and that came to an end in December. I’m ready for something new.

I reread my post on what queueing theory taught me about work life balance, which reminded me of the importance to take a few minutes for myself every day.

For more reading, check out my New Year’s resolutions in 2018, 2019, and 2021. Dijkstra’s 10 commandments of academic research also serve as potential New Year’s resolutions.

View Details

I recently attended the Coles Research Symposium on Homeland Security hosted by the Kennesaw State University Coles College of Business. The symposium was organized by Prof. Jomon Paul, and he made sure all attendees felt welcome. I gave a keynote talk entitled “New frontiers in homeland security: advances and opportunities.” The symposium was focused and […]

View Details

The state of Michigan passed Proposition 2 on November 8, 2022, a bill that introduces several voting rights including access to drop boxes. Proposition 2 will lead to the widespread use and location of drop boxes in the state of Michigan, since it requires at least one ballot drop box per 15,000 registered voters with […]

View Details

My oldest daughter started college this month, which was a milestone for her and for me. I drove her to her university and moved her into her dorm. When I said good-bye, I left her with a personalized letter expressing my confidence in her and other sentiments. I included a short list of advice at […]

View Details

I recently published an article in ORMS Today entitled “10 Principles for Changing your Name as a Mid Career Academic” that, as the name suggests, describes my process of changing my name five years ago and the lessons I learned along the way. The article expands upon an earlier blog post that I wrote in […]

View Details

I have three public outreach items to share from this summer. Details are below. I also recorded a podcast for the IISE Operations Research podcast series about OR for social good. This podcast should be released in September 2022. All my previous media appearances can be found on the “In the News” tab of this […]

View Details

I’m at the National Science Foundation (NSF) Safe and Trustworthy Computing (SaTC) Principal Investigators’ (PIs) Meeting in Arlington, VA for my grant with Prof. Jim Luedtke entitled “An Optimization Framework for Identifying Dynamic Risk Management Practices.” You can read more about our project in the NSF award abstract and the UW-Madison news release. I created […]

View Details

“[I]t seems to me that the term linear programming’ is a most unfortunate phrase for this promising technique, particularly since many possible extensions appear to be in nonlinear directions. A more general yet more descriptive term, such asbounded optimization,’ might have been a happier choice. Philip M. Morse (1953). Trends in operations research. Journal of […]

View Details

When I was a PhD student in the early 2000s, my advisor, Sheldon Jacobson, told me that some had once predicted the death of operations research. This came as a surprise to me, because it seemed like the discipline was flourishing. He agreed with me and named a few reasons why he thought operations research […]

View Details

It’s hard to believe that I started this blog fifteen years ago on April 2, 2007. Here are some milestones in the life of the blog: I published 762 posts. I started 105 drafts of blog posts that I never finished. Most of those drafts are a quick idea I saved to finish later, but […]

View Details

This year’s Final Four is set in the NCAA men’s basketball tournament, with Duke, the University of North Carolina (UNC), Kansas, and Villanova facing off this weekend. This is the first time Duke and UNC will play in the tournament. At first blush this is hard to believe when considering how often these two teams […]

View Details

Happy International Women’s Day! I encourage you to join me in celebrating women’s achievements, raising awareness against bias, and taking action for equality. I am going to focus on women in academia today, since the COVID-19 pandemic has been particularly difficult for female tenure track professors who have young children. Over the years, I’ve discovered […]

View Details

Last week I was on a panel about science communication hosted by the Women in OR & Analytics Network (WORAN), a network for female academics and practitioners created by the Operational Research Society of the UK. Marco Luebbecke (@mluebbecke) from RWTH Aachen was the other panelist. Our talk was recorded and posted on YouTube. You […]

View Details

I was honored to give the Omega Rho keynote lecture at the 2021 INFORMS Annual Meeting. My talked was entitled “A journey through public sector operations research.” My presentation was recorded and can be viewed on YouTube. Further reading: Op-Eds Travel bans can’t stop this pandemic. The Hill, March 18, 2020. Opening the economy is […]

View Details

“The secret of good writing is to strip every sentence to its cleanest components.” William Zinsser, On Writing Well In my previous post, I introduced an excerpt from On writing well by William Zinsser about how writing is work and we can learn to get better. What stuck with me from On writing well were his […]

On Writing Well: The Classic Guide to Writing Nonfiction

View Details

When I was preparing for my preliminary exam, a friend gave me a copy of the 25th anniversary edition of On writing well by William Zinsser. I read it at once, devouring it in a couple of days. It instantly became one of my favorite books and is still my favorite book about writing. Zinsser […]

View Details

In my lab meeting this month, we discussed writing operations research publications. We read How to Write About Operations Research by Gerald G. Brown at the Naval Postgraduate School, a fabulous guide for writing technical publications in the field of operations research written in 2004. The entire paper is worth reading and discussing. The paper […]

View Details

I’m honored to step into the department chair role. As of July 1, 2021, I have been the David H. Gustafson Chair of Industrial and Systems Engineering at the University of Wisconsin-Madison. Below is an article about this transition and the next chapter in my professional journey. I am grateful to follow in the footsteps […]

View Details

Operations research is a model-centric discipline. We use many mathematical models such as scheduling, assignment, facility location, inventory, and queueing that are presented in operations research textbooks. Formulating new models is often a major contribution in many of our research papers.

The models in our textbooks came into existence and were once formulated for the first time. As an applied researcher, it is important to train the students in my group in how to formulate models that are elegant and parsimonious and reflect appropriate assumptions in the real application. In a recent lab meeting, we read “On the Art of Modeling” by William T. Morris that was published in Management Science in 1967 that teaches the art of modeling.

Models can play the role of giving structure to experience. Yet we seldom encounter a model which is already available in fully satisfactory form for a given management situation, and the need for creative development or modification is almost universally experienced in management science.

Morris (1967)

Morris describes a looping procedure for creating and modifying models, which acknowledges that models are created iteratively. In each iteration, the model is tested against data or the set of assumptions that characterize it. A new version of the model is produced, which leads to a new test or comparison, which repeats until the modeling process is complete. Modeling takes time, trial and error, and experimentation.

The paper offers three “hypotheses” for creating models that are interesting. The entire paper is worth reading, and I won’t repeat them all here. Here are two parts of the discussion that I found to be useful:

Factor the system problem into simpler problems. Identify the right structure for each problem (scheduling, assignment, queueing). This requires setting aside the overarching design objective, which can be difficult for some.
Seek analogies. New problems usually have a lot in common with existing models for other applications. Here, we compare our problem at hand with previously developed models and their logical structures. Is the problem a queueing problem or an inventory problem? Is it linear?

I use both of these methods as well as some of the other modeling practices in the paper.

What is your process you use to create models?

Punk Rock Operations Research: Recent Episodes

None