Actually a relatively interesting algorithm, but I don't think the author explains it fully. The men must also rank the females. The key point is that for a match between people A and B, A has no person ranked higher than B who also ranks A higher than their current partner. it is optimal for every participant.
I'm not too familiar with residency- I wonder if hospitals submit a list of potential students they accept? How does the length of a hospital's acceptable candidates list compare to the number of hospitals a student will apply to? In the Stable Marriage Problem, each set member must rank every member of the other set.
> I'm not too familiar with residency- I wonder if hospitals submit a list of potential students they accept?
The article does mention that, "Med students and hospitals are currently ranking their top choices from these interviews." I would assume that the hospital only ranks students they interview and would consider acceptable for the program.
> Each set member must rank every member of the other set.
I would assume that they just fill in the blanks with some value that prevents matching. I don't think a hospital or a resident would be very happy with what would amount to random assignment of the leftovers.
Yes, they only rank students they interview. Those students who don't match before the rankings are exhausted "scramble"; they speed-date programs that still have openings in the hope of matching, so the leftovers are not randomly assigned. (Whether the outcome for them is better than random is hard to say.)
But isn't this exactly the Gale Shapely algorithm for stable matching? I was reading the Algorithm Design book by Kleinberg and Tardos and they introduce both the algorithm and also the fact that it's used for matching students with residencies. If it's algorithm enough for a book on algorithms I can't imagine it not matching the way it's used here.
I agree. In my algorithms class in undergrad, the Gale-Shapley algorithm (and its cousin, the Boston-Pool algorithm) were used as motivating examples of how algorithms affect our lives at the very beginning of the semester.
I don't think the "matchmaking algorithm" in the blog post actually matches the colloquial meaning of the word "Algorithm".