title: K-means algorithm variation with equal cluster size
body: <p>I'm looking for the fastest algorithm for grouping points on a map into equally sized groups, by distance. The <a href="http://en.wikipedia.org/wiki/K-means_clustering" rel="noreferrer">k-means clustering algorithm</a> looks straightforward and promising, but does not produce equally sized groups.</p>
  
  <p>Is there a variation of this algorithm or a different one that allows for an equal count of members for all clusters?</p>
  
  <blockquote>
    <p>See also: <a href="https://stackoverflow.com/questions/8796682/group-n-points-in-k-clusters-of-equal-size">Group n points in k clusters of equal size</a></p>
  </blockquote>