Samuel Hansen of ACMEscience.com hosts the Relatively Prime math podcast. Season 2 just came out – it’s definitely worth checking out [Link]. Season 2 contains five episodes. I am on the episode entitled “Just choose a spot Bob” about my blog post about how to optimally choose a parking spot.
Tag Archives: podcast and video
One of my blog posts about starting a fire at a gas station was featured on the math podcast The Other Half called “The Road Trip” by podcasters and professors Dr. Annie Rorem and Dr. Anna Haensch [Listen here] The podcast is about taking an optimal road trip (the Traveling Salesman Problem (TSP)) and rare risks associated with travel.
In The Road Trip, Anna and Annie look into the math that undergirds the great American summertime tradition of rolling down the windows, turning up the stereo, and touring the countryside by automobile.
Randy Olson has made the planning part easy by computing the optimal road trip across the U.S. His work to minimize the miles between landmarks in the lower 48 has been featured in the Washington Post and on Discovery News. In fact, Tracy Staedter of Discovery News can be credited not only with encouraging Olson to tackle this problem, but also with determining the list of landmarks he used. If you have a road trip you’d like to optimize, check out his code here.
And, because cars don’t run on math alone, we also consider the necessity of refueling on the road. In particular, we ask Laura McLay to weigh in on gas station safety, as she computes the conditional probability of blowing yourself up while you’re pumping gas.
“The Road Trip” is n excellent podcast! Thanks to Annie and Anna for doing such a great job and for being math ambassadors. I look forward to future episodes.
The Other Half is part of ACME Science, which offers several other math and science podcasts.
One thing I would like to add to the podcast is that there are real applications of the TSP and risk analysis. We academics don’t always sit up in our ivory towers coming up with silly problems to solve that are divorced from the real world. We need to be able to characterize rare risks for numerous applications (e.g., nuclear power risks) and then communicate those risks to others for managing rare but potentially catastrophic risks. I have a few links to related blog posts at the bottom of this post. Likewise, the TSP isn’t just used to plan summer road trips. It’s used by trucking and delivery companies to plan routes, in gene sequencing, for meals-on-wheels deliveries, and in emergency response after a disaster.
A second point is that we really can optimally solve many instances of the TSP, and certainly the ones used for planning road trips. We do not always have to settle for a solution that is “good enough.” It’s true that there are more feasible solutions to many problems than there are stars in the galaxy, but we don’t solve the problems by brute force. We more intelligently solve the problems using optimization algorithms such as the simplex algorithm (a linear programming algorithm) and cutting planes (an integer programming method). Optimization algorithms traverse through the search space and find the single optimal solution among trillions of possibilities sometimes in mere seconds or minutes. It’s truly astonishing and a great contribution to basic science.
If you want more, Bill Cook is the world’s expert on the TSP and he has many examples of optimal solutions on his web site, including a TSP rout of 24,978 cities. Read Bill Cook’s (@wjcook) book and blog about the TSP for more details about the TSP’s history, algorithms, and people.
- what is the (conditional) probability of exploding when filling your car up with gas?
- Type II errors are the ones that get you fired: the Atlanta edition
- operations research, disasters, and science communication
- what is the optimal false alarm rate for tornado warnings?
- the traveling salesman problem challenge for cheeseheads
- Bill Cook’s TSP talk at the University of Wisconsin-Madison
- Your ideal summer beach read: In Pursuit to the Traveling Salesman problem
I am very excited about a new project by Banafsheh Behzad (@banafsheh_b) and David Morrison (@drmorr0) promoting operations research. Their project is a YouTube channel called ORiginals: outstanding research in everyday language. I may be a bit biased because their first episode is about my research (Thanks Banafsheh and David!), but I think you will agree that the final product is gorgeous and leaves me anxious more.
Both Banafsheh and David are young OR professionals and both are already movers and shakers in our field. Banafsheh is a Professor of Information Systems at California State University, Long Beach and David is a Research Scientist and Director at a small startup. Banafsheh’s research is in healthcare and David was a finalist in the Doing Good with Good OR competition a couple of years ago. Both are very familiar with talking about OR with a societal impact, and that really comes through in their project. Their YouTube channel is brilliant, and it is great for our field! Please subscribe (do so here) and help spread the word.
I was on the 10 o’clock evening news last night on NBC15 Madison to talk about the odds of three people in Dane County winning the Supercash! lottery. There are about half a million residents, and I have no idea how many people play the lottery every day, but I was able to do a few quick back of the envelope calculations
- If everyone in Dane County plays the lottery every day (unrealistic!) then we would expect 3+ people to win in a single day to happen every 0.71 years.
- If half of everyone in Dane County plays the lottery every day (almost all the adults, still unrealistic!) then we would expect 3+ people to win in a single day to happen every 5.12 years.
- If 1 in 10 people in Dane County play the lottery every day (in the ballpark of reality) then we would expect 3+ people to win in a single day to happen every 584 years.
- If 1 in 20 people in Dane County play the lottery every day (in the ballpark of reality) then we would expect 3+ people to win in a single day to happen every 4620 years.
I am having trouble embedding the video, but you can go here to see it.
Tips for working with the media:
- You can overthink it. “Make things as simple as possible, but not simpler.” Except in this case, even simpler is good. You don’t have a couple of minutes to break apart a concept. Insightful comments that can fit in a tweet are good.
- News moves fast. I was recorded 2 hours after getting the call for the story. In that two hours, I had to take care of things at work, pick up my daughters, and go home. There was very little time for research.
- Crunch some numbers ahead of time to put things into perspective. You may only have time for back of the envelope calculations. If you don’t have all the information (like how many people play the lottery every day), make an assumption and test a few values.
- I find it helpful to explain probabilities in terms of odds (1 in 1.6 million) and expected time to observe the event (every 584 years).
- If you’re dealing with rare events, be prepared to compare the rare event to other rare events. Someone will definitely ask about the odds of getting struck by lightning.
- what is the conditional probability of being struck by lightning
- my podcast on my irrational fears, including being eaten by a bear
- a roundup of March Madness NCAA basketball tournament articles, including my appearance on NBC to discuss the perfect bracket.
Former INFORMS President Anne Robinson recently talked about operations research and analytics in a YouTube video. As President of INFORMS, she did a lot of work to promote analytics in the OR/MS community and to understand perceptions of analytics vs. operations research. I really appreciate what Anne has done for our field. Her research efforts found that people perceived operations research is a toolbox whereas analytics was perceived as an end-to-end process for data discovery, problem formulation, implementation, execution, and value delivery. This is an interesting finding.
This is Anne’s answer to the question: What is the role of OR in analytics?
“Operations research is on the top of the food chain when it comes to analytic capabilities and potential game changing results.”
I love this.
Anne’s challenge is for us to make decision-makers understand that OR is as vital and necessary as analytics. Evangelize early and often. Given the popularity of analytics, we should be able to make some inroads in educating our peers in STEM about OR, but in the long run this may be tough to do. Analytics is the new kid on the block, and it already seems to have reached widespread adoption, whereas operations research–while being at the top of the food chain–is still somewhat of a mystery to those outside of our fairly small field. Operations research has had an identity crisis for a long time, and I don’t see that coming to an end.
I applaud INFORMS decisions to “own” analytics via Analytics Certification and the Conference on Business Analytics (formerly the INFORMS Practice Conference) rather than try to solely market “operations research” to the growing analytics crowd.
What do you think?
One of the podcasts I regularly listen to (“Stuff Mom Never Told you“) recently has a series of four podcasts on women in STEM (one each for the S, T, E, and M). The engineering and math podcasts were the most interesting. Both podcasts covered many topics, so I’ll just highlight a couple of the topics discussed here.
The math podcast [Link] covered the history of women in math and focused on gender differences in math achievement (and sometimes, the lack thereof).
The engineering podcast [Link] covered pipeline issues in engineering (recruiting and retaining women). They discussed the success of industrial engineering in attracting women. This podcast will be of particular interest to readers of this blog. High school students (both girls and boys) are often unaware of what engineering is, and as a result, students who are good at math choose majors like math and physics instead of engineering. Increasingly, medicine and forensic science are attractive career options to high school students thanks to television programming. This podcast will resonate with those of us in operations research, which is even less known as a field than engineering (Many know that engineering exists, few know what engineers do. Fewer know that operations research exists(!) ).
Here are a few of my posts about women in math, science, and computing: