A specialized solver to compute the Lovász
function of a
graph is also available. As in the diagonally constrained case, such
an SDP is solved much more efficiently by the XZ method than the
XZ+ZX method. The driver script is lsdp.m and the
specialized function is flsdp.m. The five steps involved in
setting up and solving a problem are again similar to Section 3,
except for the following important differences:
,
, is
, where
is the kth edge in the graph,
and
, with
.
The user must provide a matrix G (an adjacency list with as many rows
as there are edges and 2 columns, each row of this matrix defining an edge) and
a weight vector w, with one component for each vertex of the graph.
The cost matrix C is defined by
. (The optimal value of this SDP is actually
minus the value of the
function of the graph.)
,
and
.

has the value 3, the
meaning is slightly different from the XZ+ZX case. Here,
means that the Schur complement matrix, which is symmetric for the
XZ method, was numerically indefinite or singular, i.e. Matlab's
chol routine failed or generated a zero diagonal element.
Appendix B contains sample Matlab sessions that illustrate the use of dsdp.m and lsdp.m on these special types of problems.