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Re: [Help-glpk] Why would fixed constraints lead to infeasibility?

From: Michael Hennebry
Subject: Re: [Help-glpk] Why would fixed constraints lead to infeasibility?
Date: Fri, 18 Sep 2009 22:06:04 +0400

On Fri, 18 Sep 2009, Sam Seaver wrote:

> I'm getting an "Problem has no feasible solution" error from my use of
> GLPK.  I have found I can solve this by relaxing the upper and lower
> constraints I have on one column in my constraint matrix.
> The constraints are fixed and equal:
> Col         Lower   Upper
> ATPM      8.39     8.39
> and if I relax the constrains arbitrarily, and in a small manner so
> that they are no longer equal, for example:
> Col         Lower   Upper
> ATPM     8.389     8.39
> Then glpk will return an optimal solution.

With what value for ATPM?

> What I don't understand is why I should have to do this?  Is it
> related to the tolerance of glpk, in that the difference between the
> upper and lower constraints must be more than 1e-6 or something like
> that?

GLPK does allow one to fix variables.
I suspose it's *possible* that telling it a fixed "variable" is
double bounded instead of fixed might cause it to do the wrong thing.
Probably the difficulty is elsewhere.
Is your problem almost infeasible?

Michael   address@hidden
"Pessimist: The glass is half empty.
Optimist:   The glass is half full.
Engineer:   The glass is twice as big as it needs to be."

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