R help - Feb 2008 - Quadratic Programming

Hi,

I am using solve.QP (from quadprog) to solve a standard quadratic
programming problem: min_w -0.5*w'Qw st ... I would like solve.QP to do two
things: 1) to start the optimization from a user-supplied initial
condition; i.e., from a vector w_0 that satisfies the constraints, and 2) to
return the values of the lagrange multiplieres associated with the
constraints. I did not find an obvious way in help(solve.QP). Any thoughts?

Thanks.

Jorge

	[[alternative HTML version deleted]]

>From: Jorge Aseff <jgaseff at gmail.com>
>Date: 2008/02/15 Fri PM 04:51:16 CST
>To: r-help at r-project.org
>Subject: [R] Quadratic Programming
Adrian Trapletti has a function in his tseries
package ( the name of the function escapes me ) that uses the solve.QP solver to
model some kind of quadratic portfolio problem. I don't remember if it does
exactly what you want but take a look at tseries because it's in there and
it may be of help to you.

                             Mark
>Hi,
>
>I am using solve.QP (from quadprog) to solve a standard quadratic
>programming problem: min_w -0.5*w'Qw st ... I would like solve.QP to do
two
>things: 1) to start the optimization from a user-supplied initial
>condition; i.e., from a vector w_0 that satisfies the constraints, and 2) to
>return the values of the lagrange multiplieres associated with the
>constraints. I did not find an obvious way in help(solve.QP). Any thoughts?
>
>Thanks.
>
>Jorge
>
>	[[alternative HTML version deleted]]
>
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>PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>and provide commented, minimal, self-contained, reproducible code.

G'day Jorge,

On Fri, 15 Feb 2008 17:51:16 -0500
"Jorge Aseff" <jgaseff at gmail.com> wrote:
> I am using solve.QP (from quadprog) to solve a standard quadratic
> programming problem: min_w -0.5*w'Qw st ... I would like solve.QP to
> do two things: 1) to start the optimization from a user-supplied
> initial condition; i.e., from a vector w_0 that satisfies the
> constraints, 
Not possible.  solve.QP is based on the Goldfarb-Idnani algorithm which
first calculates the unconstrained solution of the problem and then
checks for violated constraints; if such exist, then they are
iteratively enforced until all constraints are satisfied.

If you want to specify starting values (or have warm starts), then you
would need to use other kind of algorithms.
> and 2) to return the values of the lagrange multiplieres
> associated with the constraints.
See:
https://stat.ethz.ch/pipermail/r-devel/2007-December/047636.html

Hope this helps.

Best wishes,

	Berrwin

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