These kinds of algorithms tend to have equivalent descriptions as expectation maximisation or simulated annealing. I wonder if it's possible to understand their algorithm in that sense.

Though I suppose it may be as simple as expectation maximization with a friction term, since Sj = sj - a (sj - Sj).

Importantly they note that this update rule keeps the centroid within the convex hull, which is pretty important.