[SciPy-user] Linear Constrained Quadratic Optimization Problem
Tue Aug 28 15:23:05 CDT 2007
On 8/28/07, Chris Hudzik <firstname.lastname@example.org> wrote:
> I am trying to solve a quadratic optimization problem:
> minimize (x - y*p)^T * V * (x - y*p) over x,y
> x^T * t = b
> where x, t, and p are vectors; V is a symmetric matrix; and y and b are
> I am new to scipy. Can anybody point me to a scipy module to solve this?
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
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