Month: January 2010

Yo Trick! Where’ve you been?

I was annoyed at myself this morning when I realized that January was almost over and I had only 3 blog posts.  Since my goal is 3/week, it is clear that I am getting the year off on the wrong foot.   I could, of course, put in eight or so posts on being too busy to post (kinda like a tweet I had about being too busy to tweet!) but I don’t think my audience would fall for that:  being OR people, they are pretty smart and can see through such an obvious ploy.

But it has been an interesting month, so I thought I would update on some of things that are happening in my life.  Perhaps this will also help with the question “What does a faculty member do all day long?”

I’ll begin with teaching, since this is a pretty heavy teaching period, with two courses and three sections:

The first course is “Mining Data for Decision Making”, a course that I created back in 2000 for our MBA students.  This course is extremely popular with the MBAs and I ended with with full classes (80 students each) for the two sections, with about 40 on the waiting list.  After a couple less-than-stellar lectures, I got it whittled down to 7 left on the waiting list by the time the add-drop deadline came by.  One quick vignette:  In an early class, we talk about supermarket affinity cards and how much information you give supermarkets about yourself when you use their cards.  I point out that in return for that information, supermarkets give you discounts and perhaps can better tune their advertising efforts to your individual interests.  Of course, this can work against you:  if a supermarket believes that you will certainly buy a particular salsa, do you think they will give you a coupon for that salsa?  Should they give you such a coupon?  Since their actions are unclear, it is uncertain whether they are helping or hurting you with the information you give them.

That night, we got an automated call from our local supermarket saying that some hash browns we bought a few months ago were tainted with listeria (my wife’s response: “You cook once a month and even then you poison us!”).  They knew we bought the hash browns from the affinity card data, showing an advantage for using the card and providing correct contact data.

The other course I am involved with is Operations Research Implementations.  Our goal in this MBA course is to get way beyond the “four variable, three constraint” formulations and to get students doing things that look more like real-world projects.  We were lucky had had 20 students sign up, which is an ideal size for this type of course.  We chose AIMMS as our modeling package, with Gurobi as the underlying software. I am co-teaching this course with Willem van Hoeve. My main goal was to learn how to use AIMMS, and it has gone very well so far.  I also continue to be very impressed with the Gurobi solver.

For this course, students do a project (in teams), either from us or chosen on their own.  The ones we offered were

  1. Truck contracting (ala work I did with the postal service)
  2. Sports scheduling for a purpose-built little league complex
  3. Inbound distribution routing
  4. Wildlife corridor design

One group has already decided to do a project on their own:  ad placement in an online environment.  We’ll see whether other groups have their own ideas of if they are going to pick from the above).

More later on about doing academic administration, journal activities, and all the other things faculty members do.

Operations Research: Growth Industry!

NPR has a nice graphic for where job growth will occur in the next decade based on US Bureau of Labor Statistics data (the NPR site is much cooler than the graphic above). Now, operations research is a little small to appear as a dot on its own, but if you look at that little dot far to the right, showing the most job growth? That is “Management, Scientific, and Technical Consulting Services”. And what field is all of “management, scientific and technical”? Operations Research, of course! The projection is for 82.8% growth.

There are some other interesting dots that might guide those in our field. Note the big dot second from the top. That is Manufacturing, with a 9% loss in jobs. Some of that might be due to efficiencies from our field, but I suspect most is due simply to a shrinkage in importance of manufacturing to the US economy. Some of the big growth areas? Education, health care and construction with growth in the 15-25% range. This suggests that applying operations research in the service industries is going to be a big driver of growth in our field (unless we miss the boat and let another field do operations research there under a different name).

Thanks to the INFORMS Facebook Page for the pointer!

Data Mining, Operations Research, and Predicting Murders

John Toczek, who writes the PuzzlOR column for OR/MS Today  (example), has put together a new operations research/data mining challenge in the spirit of, though without the million dollar reward of, the Netflix Prize.  The Analytics X Prize is a  fascinating problem:

Current Contest – 2010 – Predicting Homicides in Philadelphia

Philadelphia is a city with 5.8 million people spread out over 47 zip codes and, like any major city, it has its share of crime.  The goal of the Analytics X Prize is to use statistical techniques and any data sets you can find to predict where crime, specifically homicides, will occur in the city.  The ability to accurately predict where crime is likely to occur allows us to deploy our limited city resources more effectively.


What I really like about this challenge is how open-ended it is. Unlike the Netflix Prize, there is no data set to be analyzed. It is up to you to determine what might be an interesting/useful/important data set. Should you analyze past murder rates? Newspaper articles? Economic indicators? Success in this might require a team that mixes those who understand societal issues with data miners and operations researchers. This, to me, makes it much more of an operations research challenge than a data mining challenge.

I also like how the Prize handles evaluation: you are predicting the future, so murders are counted after your submission. Unless you have invented time travel, there is no way to know the evaluation test set, nor can you game it like you could in the Netflix Prize (at the risk of overfitting).

I asked John why he started this prize, and he replied:

I started this project about a year ago when trying to think of ways to
attract students and people from other professions into the OR field. I
write an article in ORMS Today called the PuzzlOR which I originally
started in hopes of attracting more students to our field. OR can be a bit
overwhelming when you first get into it so I wanted a way to make it easier
for the newcomers. The puzzles I wanted to run were getting a bit out of
hand in their complexity so I needed some other place to house them.

Plus, I thought it would be good advertising for the OR field in general
and would have positive impact on the city where I live.

He’s already gotten good local press for the project. The Philadelphia City Paper ran a nice article that mentions operations research prominently:

Operations research may not sound sexy; it focuses on analytics and statistics — determining which data in a gigantic data haystack is most relevant — in order to solve big problems.

There is a monetary prize involved: $20 each month plus $100 at the end of the year. It is probably a good thing that this is not a million dollar prize. Since entries are judged based on how well they do after submission, too high a prize might lead to certain … incentives … to ensure the accuracy of your murder predictions.

The Magical Places Operations Research Can Take You

Art Benjamin of Harvey Mudd College has an article in this week’s Education Life section of the New York Times where he gives ten mathematical tricks.

I first met Art in the late 80s at, I believe, a doctoral colloquium sponsored by ORSA/TIMS (now INFORMS). Art was clearly a star: he won the Nicholson Prize (Best Student Paper) in 1988. If he had stuck with the “normal path” of being an academic researcher, I have no doubt that he would now be well known in operations research academia.

But his real passion was lightning calculation and other forms of mathematical magic and in keeping with that path, he has made himself even better known to a much broader audience. He has published three books aimed at the general audience, including one that was a Book-of-the-Month Club selection (is this unique in operations research?). He has an amazing act that he performs for a wide range of audiences.

His research has moved out of operations research  into combinatorics and combinatorial games (though these areas have a lot of overlap with OR), where he publishes prolifically and has two books aimed at professionals. His book “Proofs that Really Count” (along with Jennifer Quinn) is a great introduction to combinatorial proofs.

Art is another example of the variety of paths you can take after an operations research degree.