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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."