K-means algorithm variation with equal cluster size

Question

I\'m looking for the fastest algorithm for grouping points on a map into equally sized groups, by distance. The k-means clustering algorithm looks straightforward and promis

Answer 1

Equal size k-means is a special case of a constrained k-means procedure where each cluster must have a minimum number of points. This problem can be formulated as a graph problem where the nodes are the points to be clustered, and each point has an edge to each centroid, where the edge weight is the squared euclidean distance to the centroid. It is discussed here:

Bradley PS, Bennett KP, Demiriz A (2000), Constrained K-Means Clustering. Microsoft Research.

A Python implementation is available here.