Unable to retrieve attribute 'ObjVal', despite GRB_Optimal status

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Robert Strassen

2022年03月11日 11:15 編集済み

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Hi all,

I use C++ and try to solve a LP with a LinExpr object function and LinExpr constraints that are added in a while-loop. I noticed that sometimes the solution of my algorithm was not feasible for my purpose.

In order to debug the problem I tried to use the model.write() method which gave me an error 10005. I searched through this community and found that my solution might be unfeasible and so I checked for the GRB_IntAttr_Status Attribute (see https://support.gurobi.com/hc/en-us/community/posts/4403281044113-Error-10005-Unable-to-retrieve-attribute-X-). In my case, this attribute is always set to GRB_OPTIMAL. As far as I know, the write() method also writes everything correctly into my lp-file but I still get the error (after writing everything into the output file).

To give a bit of context: In my case the theoretical number of constraints grows exponentially with the problem size and therefore I try to add single constraints in a while-loop until a special condition ist met. Sometimes I get a LP-solution which works as expected and then I don't have the above-mentioned problem when using the write-method, but sometimes this problem occurs and this is always the case, when the LP-solution is wrong and violates constraints that should have been added.

Does anybody know what might be my problem here?

 

Edit: I think I found the problem: I have the problem that sometimes I add a new constraint, but after that I don't call model.optimize() again. Might this lead to the given error?

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  Simranjit Kaur

  • Gurobi Staff

  2025年11月16日 23:42

  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 try Gurobot, our chatbot interface offering instant, expert-level support.
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  Jaromił Najman

  • Gurobi Staff

  2022年03月11日 15:44

  Hi Robert,

  I think I found the problem: I have the problem that sometimes I add a new constraint, but after that I don't call model.optimize() again. Might this lead to the given error?

  Probably yes. If the constraint cuts of the previous solution and you don't re-optimize, it is possible that the previous solution is lost. However, I am just guessing here. If calling model.optimize() does not help, could you share a minimal working example reproducing the issue?

  Best regards, 
  Jaromił

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