Thanks Rafael for your answer,
I changed the tolerances, but it did not help. I still get negative MIP gaps. What is special about my model is that it is a two objectice optimization problem that uses the weighted sum approach to make the objetice funciton 1-dimensional (and normalize the two objectices by the optimal value of their single-objectice problem). Maybe this causes this strange behaviour by CPLEX?
What is also really strinking, is that even after CPLEX has found solutions that have a negative MIP gap, is sometimes proceeds searching for furher solutions with even lover MIP gap (“higher” neative value) altough the tolerance is set to 0.01%. This is extremely strange. You can see this behaviour in the newly attached log file “CPLEX_LOG_2.txt”.
Is there a way how I can tell CPLEX to neglect the solutions with negative MIP gap?
Source: Re: Negative MIP gap