Lagrangian Relaxation bound greater than optimal solution
Ongoing
I am working on a Lagrangian relaxation for a minimization MIP.
Everything seemed to be working fine before I started to run a batch of instances.
Checking the log results for one of the instances I found out that the lower bound given by the LR algorithm was greater than my optimal objective.
One of my concerns, beyond wrong coding from my part, is the chance that the solver is removing columns or doing any other stuff to speed up optimization that is only feasible because of the relaxed constraints.
I saw this kind of problem before when a friend was implementing a branch and cut with cplex without changing a solver parameter.
Is there any parameters set that I should deactivate, like presolve, cutting planes etc?
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The solver may remove some variables and do other things as part of the presolve, so if you are curious to see if this plays any role here you can try setting Presolve = 0 to switch it off (mind you, often this results in longer solution times).
Hope this helps.
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Hi,I'm trying to minimize an MIP model employing a Lagrangian relaxation approach. However, I've encountered an issue where, in certain instances, the lower bound (resulting from the Lagrangian sub-problem) surpasses both the upper bound (resulting from the Master problem) and the optimal solution of the original problem. Consequently, no Lagrangian bound is obtained, as the lower bound continues to outpace the upper bound, while the upper bound steadily decrease. I tried to enhance the accuracy of the models, the issue is still there. The Presolve = 0 and Cuts =0 doesn't work either.
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