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

[Sam Seaver]

Dear all,

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.

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?

Thanks
Sam
-- 
Graduate student
Northwestern University
Interdisciplinary Biological Sciences (IBiS) Program
2205 Tech Drive (Room 2-108 )
Evanston, IL 60208, US

http://amaral.northwestern.edu/people/seaver/
address@hidden