Hello Mark,
I am not sure to have understood well your question. Do you talk about sequential quadratic programming (SQP) or just 'how to solve' a quadratic problem?
Do your problem have this form: Minimize f(x): { x in X, g(x) <= 0, h(x) <= 0 }? so SQP would be suitable to solve your problem. The known method is with lagrangian multipliers. Anyway, I dont know any open source libraries which have it.
Regards
Frédéric Degraeve
-----Original Message-----
From: [hidden email] [mailto:[hidden email]] On Behalf Of Mark joshi
Sent: lundi 7 mai 2007 02:10
To: [hidden email]
Subject: [Quantlib-dev] quadratic programming
Dear All,
I have an idea how to reduce the LMM calibration to a quadratic
programming question.
So
1) is there any quadratic programming in quantlib already?
2) does anyone know anything about it?
3) does anyone have any views on how it ought to be done?
The problem is pretty simple: solve a couple of quadratics in
n-variables, whilst minimizing a third.
best
mark
--
Assoc Prof Mark Joshi
Centre for Actuarial Studies
University of Melbourne
My website is <a href="http://www.markjoshi.com" target="_blank" onclick="return top.js.OpenExtLink(window,event,this)">www.markjoshi.com
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