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I am experimenting with Dip and solving a simple plant location problem. In my approach, there is a block (relaxed constraint set) for each plant. There is a relaxed constraint set for each i (plant) and the relaxed constraints for block i are:
x_{ij} \le y_{i} for all j
In this case the y_{i} is a binary variable so the sub-problem is bounded. However I get the error
Error: CBC IP solver 2nd status = 7
COIN Exception [ CBC solver 2nd status ] at ../../../Dip/src/DecompModel.cpp:L330 in DecompAlgoModel::solveOsiAsIp
If I add upper bounds of 1 on the x_{ij} variables it works and runs to completion with the correct optimal solution. However, it seems like I should not have to do this since the constraints x_{ij} \le y_{i} with y_{i} having an upper bound imply this.
Thanks
The text was updated successfully, but these errors were encountered:
Comment by @mgalati13 created at 2010-09-04 03:30:54
Kipp - please tell me how to repeat this issue. Are the constraints x <= y and y in {0,1} in the subproblem that is being declared unbounded? If the constraints x<=y are just in the master and not in the subproblems, then your subproblem might still be unbounded without the explicit bounds on x. You can use LogDumpModel=2 to see the subproblems.
Issue created by migration from Trac.
Original creator: kmartin
Original creation time: 2010-08-09 01:38:33
I am experimenting with Dip and solving a simple plant location problem. In my approach, there is a block (relaxed constraint set) for each plant. There is a relaxed constraint set for each i (plant) and the relaxed constraints for block i are:
x_{ij} \le y_{i} for all j
In this case the y_{i} is a binary variable so the sub-problem is bounded. However I get the error
Error: CBC IP solver 2nd status = 7
COIN Exception [ CBC solver 2nd status ] at ../../../Dip/src/DecompModel.cpp:L330 in DecompAlgoModel::solveOsiAsIp
If I add upper bounds of 1 on the x_{ij} variables it works and runs to completion with the correct optimal solution. However, it seems like I should not have to do this since the constraints x_{ij} \le y_{i} with y_{i} having an upper bound imply this.
Thanks
The text was updated successfully, but these errors were encountered: