Closed Ashim-Khanal closed 3 months ago
Following this solution worked
https://github.com/IBMDecisionOptimization/docplex-examples/issues/79#issuecomment-1277563364
c = m.get_cplex()
best_bound = c.solution.MIP.get_best_objective()
Thanks
I am trying to retrieve the best bound (after certain specified run time) for a second-order cone program model with quadratic constraints. Since the model is not MILP, the method: "m.get_solve_details().best_bound" did not work.
Please help to get the best bound when there are quadratic constraints.