> I used glpsol to solve the linear relaxed version of a MIP problem ( all > variables in my problem are 0 or 1) and output the solution using -o > flag. What I want is to get all those variables which have been set to > either 0 or 1 as a part of the solution and do not have a fractional > value. In the output file , I extracted all the column ids having value 0 > or 1 and added these as a new set of constraints to the original MIP > problem by fixing the variables as 0 or 1 according to the relaxed > solution. > > > Thus, this new MIP problem should surely be feasible right?
Not mip. Its relaxation must remain optimal (ergo, feasible). > > I did that but I found the new MIP problem to be infeasible. I dont know > why this is happening. The problem instance is present at > http://www.cse.ohio-state.edu/~khannag/bip_8_20_new.lp. > > The solution I get when I run the relaxed version of the problem is > present at http://www.cse.ohio-state.edu/~khannag/solution > > In this solution file, I took the value for column name under the > activity label as their solution value. Based on my > interpretation of the output file, 9409 variables out of 10244 were either > 0 or 1 according to the number under the Activity Label in the solution > file. I added these as constraints to the original MIP but it becomes > infeasible. > > Could you help me figure out the problem? Probably you made a mistake somewhere. Try checking your code. If you fix some variables at the values they have in the optimal point, the lp solution must remain optimal. _______________________________________________ Help-glpk mailing list [email protected] http://lists.gnu.org/mailman/listinfo/help-glpk
