
From:  Joey Rios 
Subject:  [Helpglpk] Many basic vars = 0, many nonbasic are on upperbound 
Date:  Thu, 11 Jun 2009 19:26:05 0700 
My decision variables are all binary. During the solve process (for the relaxation) many of the basic variables have a value of 0.0. This implies degeneracy, which I feel somewhat comfortable with. At the same time, many of my nonbasic variables return GLP_NU (nonbasic variable on its upper bound, i.e. primal value is 1) when I try glp_get_col_stat(). I'm trying to get a better understanding of what this means. Nothing in my model is broken and the GLPK chugs along and provides the correct answer, so I guess I'm just asking for a little clarification on what "nonbasic on its upper bound" means in terms of the simplex algorithm. My variables are often part of a convex combination, so the sum of some subset of them needs to be 1. It seems odd that one of them from this subset would be basic with a value of zero and another is nonbasic with a value of 1. I'm trying to understand what algorithmic paths might be taken to get to such a solution. I know the question is a tad vague, but any insight is appreciated. Thanks, Joey HotmailÂ® has evergrowing storage! Donâ€™t worry about storage limits. Check it out. 
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