Genius. My only comment is in how you measure the value of an address. It seems very likely that your algorithm would converge to areas that are only centrally located. Perhaps it could be improved if the algorithm took an input of common routes and times, then tried to find an optimal location for these routes. This way the algorithm could be scaled as needed and provide a more realistic scenario. Is this something…
So I did my own analysis: I calculated the travel time from every address to every other address in Helsinki around 7:30-8:00am (about 30 billion searches total!). Then I calculated the (weighted) average travel time to anywhere in the city, using amount of jobs in the target area as weight.
That would seemingly bias towards centrally-located addresses (travel time & number of jobs), and his heat maps seem to show this. I believe you could pretty easily duplicate what he's doing with a few dozen randomly sampled routes. Or is there more to it?