From 987b40addaa4d9d6740b9f8899df9d9c837b583b Mon Sep 17 00:00:00 2001 From: ZedongPeng Date: Tue, 22 Aug 2023 17:09:36 -0400 Subject: [PATCH] add comments for optimalitytarget --- pyomo/contrib/mindtpy/algorithm_base_class.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/pyomo/contrib/mindtpy/algorithm_base_class.py b/pyomo/contrib/mindtpy/algorithm_base_class.py index 400d74be87f..01c4dada354 100644 --- a/pyomo/contrib/mindtpy/algorithm_base_class.py +++ b/pyomo/contrib/mindtpy/algorithm_base_class.py @@ -2562,6 +2562,11 @@ def initialize_subsolvers(self): # We don't need to solve the regularization problem to optimality. # We will choose to perform aggressive node probing during presolve. self.regularization_mip_opt.options['mip_strategy_presolvenode'] = 3 + # When using ROA method to solve convex MINLPs, the Hessian of the Lagrangean is always positive semidefinite, + # and the regularization subproblems are always convex. + # However, due to numerical accuracy, the regularization problem ended up nonconvex for a few cases, + # e.g., the smallest eigenvalue of the Hessian was slightly negative. + # Therefore, we set the optimalitytarget parameter to 3 to enable CPLEX to solve nonconvex MIQPs in the ROA-L2 and ROA-∇2L methods. if config.add_regularization in {'hess_lag', 'hess_only_lag'}: self.regularization_mip_opt.options['optimalitytarget'] = 3 elif config.mip_regularization_solver == 'gurobi':