[Ipopt] Suggestions for a quadratic programming solver?

[Sean C McDuffee]

If you can't compute the hessians, MOOCHO in the Trilinos package uses 
reduced space sqp methods.  It can solve large, equality and inequality 
constrained, non-convex optimizations.

http://trilinos.sandia.gov/packages/moocho/

On 02/07/2013 12:00 PM, ipopt-request at list.coin-or.org wrote:
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Thu, 7 Feb 2013 15:58:52 +0100
> From: Antonello Lobianco<antonello at lobianco.org>
> To: ipopt<ipopt at list.coin-or.org>
> Subject: [Ipopt] Suggestions for a quadratic programming solver?
> Message-ID:
> 	<CAOibvJEWJB5TtJ0fy9T38nMqGNvVACMVS-ca0_=mpDXX8qVkvQ at mail.gmail.com>
> Content-Type: text/plain; charset="iso-8859-1"
>
> Hello.. I use normally ipopt but for a project I need a solver for a
> Quadratic Problem (so I don't need to pass all the extra-information for
> general nonlinear programming.. hessian, jacobian..)
>
> For LP I use GLPK, but I am now lost on what to use for QP.. within the
> COIN-OR projects I can see Clp, but from the manual I got that QP is not at
> his core...
> Then I found JOptimizer, but again I have no idea of the performances nor
> how it will be easy to link a java program from a C++ program (I never used
> Java)..
>
> Any suggestions? I would prefer to find an open source fast QP solver
> working on Linux/Win (MinGW).
>   Thank you...
>