MIP solution process - updating the incumbent objective value

Answered

Charitha Buddhika Heendeniya

December 18, 2019 10:10

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Dear community,

I have a question about the MIP solution process, something I observed during a simulation. In the following image, you see that the incumbent objective bound (which I understand as the upper bound of the objective) is not updated even when the current node has a better objective value in this minimization problem. This I don't understand. To me, if there is already a better solution that is feasible, then that should be the upper bound to the objective value. Can anyone explain to me this behavior?

Regards

Buddi

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• Official comment

  

  Simranjit Kaur

  • Gurobi Staff

  December 06, 2024 00:51

  This post is more than three years old. Some information may not be up to date. For current information, please check the Gurobi Documentation or Knowledge Base. If you need more help, please create a new post in the community forum. Or why not try our AI Gurobot?.
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  Silke Horn

  • Gurobi Staff

  December 31, 2019 10:35

  In the MIP process log, the incumbent column shows the objective value of the current best feasible solution. The node objective column shows the objective of the relaxation of the node. This does not mean that there is a feasible solution for the MIP model with this objective. Most of the time, the solution of the node relaxation will violate some of the integrality constraints. (In fact, you can see the number of integrality constraints violated by this solution in the IntInf column.)

  You can find more information about the MIP log here.

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