[SciPy-user] Linear Constrained Quadratic Optimization Problem

Dominique Orban dominique.orban@gmail....
Tue Aug 28 15:23:05 CDT 2007


On 8/28/07, Chris Hudzik <hudzik@gmail.com> wrote:
>
> I am trying to solve a quadratic optimization problem:
>
> minimize (x - y*p)^T * V * (x - y*p) over x,y
> s.t.
> x^T * t = b
>
> where x, t, and p are vectors; V is a symmetric matrix; and y and b are
> scalars.
>
> I am new to scipy.  Can anybody point me to a scipy module to solve this?


Hi Chris,

I don't think there is anything specifically for quadratic programs in
SciPy. In NLPy, you can solve it using the projected conjugate gradient
algorithm (ppcg). I will commit an update tonight so you can try it out.

Note that if V is not positive semi-definite, your problem may be unbounded
below.

Cheers,
Dominique
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