The Euclidean Steiner tree problem is to find the tree with minimal
Euclidean length spanning a set of fixed points in the plane, allowing
the addition of auxiliary points to the set (Steiner points).  The
problem is NP-hard, so polynomial-time heuristics are desired.  We
present two such heuristics, both of which utilize an efficient method
for computing a locally optimal tree with a given topology.  The first
systematically inserts Steiner points between edges of the minimal
spanning tree meeting at angles less than 120 degrees, performing a
local optimization at the end.  The second begins by finding the
Steiner tree for three of the fixed points.  Then, at each iteration,
it introduces a new fixed point to the tree, connecting it to each
possible edge by inserting a Steiner point, and minimizes over all
connections, performing a local optimization for each.  We present a
variety of test cases that demonstrate the strengths and weaknesses of
both algorithms.