  Quadratic programmingis a class of constrained optimization problem with
quadratic objective functions and linear constraints. It has applications in
many areas and is also used to solve nonlinear optimization problems. This
article focuses on the equality constrained quadratic programs whose constraint
matrices are block diagonal. Using the direct solution method, we propose a new
pivot selection algorithm for the factorization of the Karush-Kuhn-Tucker(KKT)
matrix for this problem that maintains the sparsity and stability of the
problem. Our experiments show that our pivot selection algorithm appears to
produce no fill-ins in the factorizationof such matrices. In addition, we
compare our method with MA57 and find that the factors produced by our
algorithm are sparser.
