Just in time for the holidays, there is a very nice competition at Kaggle: The Traveling Santa Problem. The problem was devised by the ever-creative Bob Bosch, about whom I have written before. The problem is an interesting variant on the Traveling Salesman Problem. Given a set of points and distances between them, the TS(alesman)P is to find the shortest cycle through all the points. The TS(alesman)P would not be a great competition problem: you could save the effort and just send the prize to my soon-to-be-neighbor Bill Cook with his Concorde code.

The TS(anta)P asks for *two* disjoint cycles, with a goal of minimizing the longer of the two. Of course, there is a clear explanation of why Santa wants this:

Santa likes to see new terrain every year–don’t ask, it’s a reindeer thing–and doesn’t want his route to be predictable.

OK, maybe it not so clear. But what Santa wants, Santa gets.

There is just one instance to work with, and it is a monster with 150,000 points. It turns out that the points are not randomly scattered throughout the plane, nor do they seem to correspond to real cities. I won’t spoil it here, but there is a hint at the kaggle discussion boards.

There are prizes for the best solution by the end of the competition (January 18, 2013) and, most interestingly, at a random date to be chosen between December 23 and January 17. The $3000 in prizes would certainly make a nice Christmas bonus (that is 7.5 Lego Death Stars!). You can check out the full rules, leaderboard, discussion, and more at the competition site.

I personally find this competition *much* more interesting than the data-mining type competitions like the General Electric sponsored Flight Quest (which is certainly not uninteresting). In Flight Quest, the goal is to predict landing times for planes. This is all fine and good, but as an operations researcher, I want to make some decisions to change those times to make the system work better. Helping Santa avoid ennui might not be particularly realistic but it is much better than simply predicting when my Christmas toys arrive.

If we can get a good turnout for the Santa problem, perhaps we can see more optimization competitions, or better yet, competitions that combine data mining with optimization.