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QPOPT
(invented by Philip E. Gill,
Walter Murray and Michael A.
Saunders) is a software package
for solving dense linear and
quadratic programs. If the quadratic
objective function is convex
(definite or semi definite),
the solution obtained is a global
optimum. For non-convex problems,
the solution may be a local
optimum or a dead-point (or
unbounded).
The
quadratic form x'Qx is defined
by a user routine that computes
Qx for a given vector x. (Hence
some advantage arises if Q is
sparse.) Linear constraints
and bounds on the variables
are treated separately by an
active-set method. If the problem
has no feasible solution, QPOPT
minimizes the sum of the constraint
and bound violations.
If
your quadratic is positive definite
or semi definite (typically
x'A'Ax + linear terms) you may
want to consider LSSOL.
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