> I am quoting an almost three year-old-e-mail of this list about the
> deletion of active constraints in a LP, keeping the current basis in
> order not to solve the model from scratch. I used this method in my
> algorithm (removing the constraint bounds: GLP_FR), but I don #39;t
> understand a point: when I solve the LP again, the first solution (at
> iteration 0) has a lower objective (all right) but the value of the
> infeasibility increases. How is it possible that the infeasibility
> increases although I removed a constraint? I am (still) using the GLPK
> version 4.38.

Though you make the constraint redundant changing its type to GLP_FR,
it remains active in the current basis. In glpk (as in many other lp
packages) auxiliary variables of active unbounded rows being non-basic
are fixed at zero. Thus, if you remove an active *non-zero* bound, the
primal value of the auxiliary variable changes that may cause primal
infeasibility of the current basis.




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