Remove debugging. Fix unit test. Change default for cut_change_threshold

Author: chris-maes

cpp/include/cuopt/linear_programming/mip/solver_settings.hpp

@@ -95,7 +95,7 @@ class mip_solver_settings_t {
   i_t knapsack_cuts             = -1;
   i_t strong_chvatal_gomory_cuts      = -1;
   i_t reduced_cost_strengthening      = -1;
-  f_t cut_change_threshold            = 1e-3;
+  f_t cut_change_threshold            = -1.0;
   f_t cut_min_orthogonality           = 0.5;
   i_t mip_batch_pdlp_strong_branching = 0;
   i_t num_gpus                        = 1;

cpp/src/branch_and_bound/branch_and_bound.cpp

@@ -2143,7 +2143,7 @@ mip_status_t branch_and_bound_t<i_t, f_t>::solve(mip_solution_t<i_t, f_t>& solut
       i_t num_cuts = cut_pool.get_best_cuts(cuts_to_add, cut_rhs, cut_types);
       if (num_cuts == 0) { break; }
       cut_info.record_cut_types(cut_types);
-#if 1
+#ifdef PRINT_CUT_POOL_TYPES
       cut_pool.print_cutpool_types();
       print_cut_types("In LP      ", cut_types, settings_);
       printf("Cut pool size: %d\n", cut_pool.pool_size());
@@ -2343,7 +2343,7 @@ mip_status_t branch_and_bound_t<i_t, f_t>::solve(mip_solution_t<i_t, f_t>& solut
       f_t change_in_objective = root_objective_ - last_objective;
       const f_t factor        = settings_.cut_change_threshold;
       const f_t min_objective = 1e-3;
-      if (0 &&
+      if (factor > 0.0 &&
           change_in_objective <= factor * std::max(min_objective, std::abs(root_relax_objective))) {
         settings_.log.printf(
           "Change in objective %.16e is less than 1e-3 of root relax objective %.16e\n",

cpp/src/math_optimization/solver_settings.cu

@@ -74,7 +74,7 @@ solver_settings_t<i_t, f_t>::solver_settings_t() : pdlp_settings(), mip_settings
     {CUOPT_MIP_RELATIVE_GAP, &mip_settings.tolerances.relative_mip_gap, f_t(0.0), f_t(1e-1), f_t(1e-4)},
     {CUOPT_PRIMAL_INFEASIBLE_TOLERANCE, &pdlp_settings.tolerances.primal_infeasible_tolerance, f_t(0.0), f_t(1e-1), std::max(f_t(1e-10), std::numeric_limits<f_t>::epsilon())},
     {CUOPT_DUAL_INFEASIBLE_TOLERANCE, &pdlp_settings.tolerances.dual_infeasible_tolerance, f_t(0.0), f_t(1e-1), std::max(f_t(1e-10), std::numeric_limits<f_t>::epsilon())},
-    {CUOPT_MIP_CUT_CHANGE_THRESHOLD, &mip_settings.cut_change_threshold, f_t(0.0), std::numeric_limits<f_t>::infinity(), f_t(1e-3)},
+    {CUOPT_MIP_CUT_CHANGE_THRESHOLD, &mip_settings.cut_change_threshold, f_t(-1.0), std::numeric_limits<f_t>::infinity(), f_t(-1.0)},
     {CUOPT_MIP_CUT_MIN_ORTHOGONALITY, &mip_settings.cut_min_orthogonality, f_t(0.0), f_t(1.0), f_t(0.5)}
    };
 

cpp/tests/mip/cuts_test.cu

@@ -93,7 +93,7 @@ TEST(cuts, test_cuts_1)
   // Expected objective value from documentation example is approximately -28
   EXPECT_NEAR(-28, obj_val, 1e-3);
 
-  EXPECT_EQ(solution.get_num_nodes(), 0);
+  EXPECT_LE(solution.get_num_nodes(), 2);
 }
 
 // Problem data for the mixed integer linear programming problem