Have you thought of using some of the scipy libs for this tasks?

http://docs.scipy.org/doc/scipy/reference/optimize.html


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2009/1/14 Luca Dall'Olio <luca.dallolio@gmail.com>
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Today's Topics:

   1. Re: constrained, parametric optimization (Richard B. Kreckel)


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Message: 1
Date: Wed, 14 Jan 2009 10:29:40 +0100
From: "Richard B. Kreckel" <kreckel@ginac.de>
Subject: Re: [GiNaC-list] constrained, parametric optimization
To: GiNaC discussion list <ginac-list@ginac.de>
Message-ID: <496DB084.2060308@ginac.de>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed

Luca Dall'Olio wrote:
  
I am developing a computer program which needs to solve a constrained,
parametric optimisation, something like :

meaning to calculate min(x) such as y = b*x+a and x <= c and x >=0
where x and y are variables, a, b, c are constant but unknown parameters.
Since the problem is calculated at runtime from my computer program and
changes every time, I think I need to solve it with some form of constrained
programming with a symbolic result.

I could see something like this in mathematica :

http://reference.wolfram.com/mathematica/ref/Minimize.html#61381153

but I would like to keep my program free and open source, so I would like to
use a free library for this...

could you please tell me if I can do this using ginac?
    
GiNaC isn't prepared to do constrained optimization.
  
thank you very much for saving me a lot of (unsuccessful) time searching :-)
I suppose that the example you posted above isn't the most general case 
you are aiming at. 
  
yes, you are right

 
Because if it is, you can of course do that manually.
However, if the equations start containing powers of x, things become 
more nasty.
  
I agree, I could live with limitations such as "only linear objective function, only inequality constraints ..." or things like that, but I need a parametric input (and so a symbolic result)
Regards
    -richy.
  

Best regards,
Luca

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