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How can I inherit branching tree from previous optimization after adding continuous variables



1 comment

  • Maliheh Aramon
    Gurobi Staff Gurobi Staff

    Hi Yudi, 

    As long as you do not call the model.reset() method before adding the new variables and constraints, the next call to the model.optimize() method will have access to all the information that affected the solution process such as branching priorities, MIP starts from the previous call to the model.optimize() call. 

    Please be aware that depending on the model modifications done, the extent the previous history speeds the next optimization process varies. For example, if adding the new variables and the new constraints makes the previous optimal solution infeasible, Gurobi will discard the current optimal solution and will try to find a new incumbent feasible for the modified search space.


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