List of user-set options: Name Value used derivative_test = second-order yes derivative_test_print_all = yes yes hessian_constant = yes yes jac_d_constant = yes yes max_iter = 500 yes output_file = ipopt_log yes print_level = 12 yes print_user_options = yes yes List of options: Name Value # times used derivative_test = second-order 1 derivative_test_print_all = yes 1 hessian_constant = yes 1 jac_d_constant = yes 1 max_iter = 500 1 output_file = ipopt_log 1 print_level = 12 2 print_user_options = yes 1 ****************************************************************************** This program contains Ipopt, a library for large-scale nonlinear optimization. Ipopt is released as open source code under the Eclipse Public License (EPL). For more information visit http://projects.coin-or.org/Ipopt ****************************************************************************** NOTE: You are using Ipopt by default with the MUMPS linear solver. Other linear solvers might be more efficient (see Ipopt documentation). This is Ipopt version 3.9stable, running with linear solver mumps. Starting derivative checker for first derivatives. grad_f[ 0] = -2.5298440504165775e+001 ~ -2.5298440261748244e+001 [9.582e-009] jac_g [ 0, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] jac_g [ 1, 0] = 1.0000000000000000e+000 v ~ 9.9999999794263339e-001 [2.057e-009] grad_f[ 1] = 2.5298440504165775e+001 ~ 2.5298441396545609e+001 [3.527e-008] jac_g [ 0, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] jac_g [ 1, 1] = -1.0000000000000000e+000 v ~ -1.0000000046863908e+000 [4.686e-009] grad_f[ 2] = 0.0000000000000000e+000 ~ 0.0000000000000000e+000 [0.000e+000] jac_g [ 0, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] jac_g [ 1, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] grad_f[ 3] = 0.0000000000000000e+000 ~ 0.0000000000000000e+000 [0.000e+000] jac_g [ 0, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] jac_g [ 1, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] grad_f[ 4] = 0.0000000000000000e+000 ~ 0.0000000000000000e+000 [0.000e+000] jac_g [ 0, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] jac_g [ 1, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] grad_f[ 5] = -2.6103518784142580e+001 ~ -2.6103521122422535e+001 [8.958e-008] jac_g [ 0, 5] = 1.0000000000000000e+000 v ~ 9.9999999947364415e-001 [5.264e-010] jac_g [ 1, 5] = 1.0000000000000000e+000 v ~ 1.0000000827403710e+000 [8.274e-008] Starting derivative checker for second derivatives. obj_hess[ 0, 0] = 2.0000000000000000e+000 v ~ 1.9999999958852668e+000 [2.057e-009] obj_hess[ 0, 1] = -2.0000000000000000e+000 v ~ -1.9999999958852668e+000 [2.057e-009] obj_hess[ 0, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 0, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 0, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 0, 5] = 2.0000000000000000e+000 v ~ 1.9999999958852668e+000 [2.057e-009] obj_hess[ 1, 0] = -2.0000000000000000e+000 v ~ -2.0000000093727817e+000 [4.686e-009] obj_hess[ 1, 1] = 2.0000000000000000e+000 v ~ 2.0000000093727817e+000 [4.686e-009] obj_hess[ 1, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 1, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 1, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 1, 5] = -2.0000000000000000e+000 v ~ -2.0000000093727817e+000 [4.686e-009] obj_hess[ 2, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 2, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 2, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 2, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 2, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 2, 5] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 3, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 3, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 3, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 3, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 3, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 3, 5] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 4, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 4, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 4, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 4, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 4, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 4, 5] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 5, 0] = 2.0000000000000000e+000 v ~ 2.0000001654807420e+000 [8.274e-008] obj_hess[ 5, 1] = -2.0000000000000000e+000 v ~ -2.0000001654807420e+000 [8.274e-008] obj_hess[ 5, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 5, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 5, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] obj_hess[ 5, 5] = 4.0000000000000000e+000 v ~ 4.0000003309614840e+000 [8.274e-008] 0-th constr_hess[ 0, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 0, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 0, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 0, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 0, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 0, 5] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 1, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 1, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 1, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 1, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 1, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 1, 5] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 2, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 2, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 2, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 2, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 2, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 2, 5] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 3, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 3, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 3, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 3, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 3, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 3, 5] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 4, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 4, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 4, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 4, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 4, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 4, 5] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 5, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 5, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 5, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 5, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 5, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 0-th constr_hess[ 5, 5] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 0, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 0, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 0, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 0, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 0, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 0, 5] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 1, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 1, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 1, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 1, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 1, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 1, 5] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 2, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 2, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 2, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 2, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 2, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 2, 5] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 3, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 3, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 3, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 3, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 3, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 3, 5] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 4, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 4, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 4, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 4, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 4, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 4, 5] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 5, 0] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 5, 1] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 5, 2] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 5, 3] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 5, 4] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] 1-th constr_hess[ 5, 5] = 0.0000000000000000e+000 v ~ 0.0000000000000000e+000 [0.000e+000] No errors detected by derivative checker. Number of nonzeros in equality constraint Jacobian...: 0 Number of nonzeros in inequality constraint Jacobian.: 12 Number of nonzeros in Lagrangian Hessian.............: 36 Scaling parameter for objective function = 1.000000e+000 objective scaling factor = 1 No x scaling provided No c scaling provided No d scaling provided DenseVector "original x_L unscaled" with 0 elements: DenseVector "original x_U unscaled" with 0 elements: DenseVector "original d_L unscaled" with 2 elements: original d_L unscaled[ 1]=0.0000000000000000e+000 original d_L unscaled[ 2]=1.0000000000000000e+000 DenseVector "original d_U unscaled" with 0 elements: DenseVector "modified x_L scaled" with 0 elements: DenseVector "modified x_U scaled" with 0 elements: DenseVector "modified d_L scaled" with 2 elements: modified d_L scaled[ 1]=-1.0000000000000000e-008 modified d_L scaled[ 2]=9.9999998999999995e-001 DenseVector "modified d_U scaled" with 0 elements: DenseVector "initial x unscaled" with 6 elements: initial x unscaled[ 1]=0.0000000000000000e+000 initial x unscaled[ 2]=0.0000000000000000e+000 initial x unscaled[ 3]=0.0000000000000000e+000 initial x unscaled[ 4]=0.0000000000000000e+000 initial x unscaled[ 5]=0.0000000000000000e+000 initial x unscaled[ 6]=0.0000000000000000e+000 Initial values of x sufficiently inside the bounds. Moved initial values of s sufficiently inside the bounds. DenseVector "original vars" with 2 elements: original vars[ 1]=0.0000000000000000e+000 original vars[ 2]=9.9999998999999995e-001 DenseVector "new vars" with 2 elements: new vars[ 1]=9.9999900000000003e-003 new vars[ 2]=1.0099999899999998e+000 CompoundVector "RHS[ 0]" with 4 components: Component 1: DenseVector "RHS[ 0][ 0]" with 6 elements: RHS[ 0][ 0][ 1]=2.0000000000000000e+000 RHS[ 0][ 0][ 2]=-2.0000000000000000e+000 RHS[ 0][ 0][ 3]=-0.0000000000000000e+000 RHS[ 0][ 0][ 4]=-0.0000000000000000e+000 RHS[ 0][ 0][ 5]=-0.0000000000000000e+000 RHS[ 0][ 0][ 6]=2.0000000000000000e+000 Component 2: DenseVector "RHS[ 0][ 1]" with 2 elements: RHS[ 0][ 1][ 1]=1.0000000000000000e+000 RHS[ 0][ 1][ 2]=1.0000000000000000e+000 Component 3: DenseVector "RHS[ 0][ 2]" with 0 elements: Homogeneous vector, all elements have value 0.0000000000000000e+000 Component 4: DenseVector "RHS[ 0][ 3]" with 2 elements: Homogeneous vector, all elements have value 0.0000000000000000e+000 CompoundSymMatrix "KKT" with 4 rows and columns components: Component for row 0 and column 0: SumSymMatrix "KKT[0][0]" of dimension 6 with 2 terms: Term 0 with factor 0.0000000000000000e+000 and the following matrix: SymTMatrix "Term: 0" of dimension 6 with 36 nonzero elements: Uninitialized! Term 1 with factor 1.0000000000000000e+000 and the following matrix: DiagMatrix "Term: 1" with 6 rows and columns, and with diagonal elements: DenseVector "Term: 1" with 6 elements: Homogeneous vector, all elements have value 1.0000000000000000e+000 Component for row 1 and column 0: This component has not been set. Component for row 1 and column 1: DiagMatrix "KKT[1][1]" with 2 rows and columns, and with diagonal elements: DenseVector "KKT[1][1]" with 2 elements: Homogeneous vector, all elements have value 1.0000000000000000e+000 Component for row 2 and column 0: GenTMatrix "KKT[2][0]" of dimension 0 by 6 with 0 nonzero elements: Component for row 2 and column 1: This component has not been set. Component for row 2 and column 2: DiagMatrix "KKT[2][2]" with 0 rows and columns, and with diagonal elements: DenseVector "KKT[2][2]" with 0 elements: Homogeneous vector, all elements have value -0.0000000000000000e+000 Component for row 3 and column 0: GenTMatrix "KKT[3][0]" of dimension 2 by 6 with 12 nonzero elements: KKT[3][0][ 1, 1]=0.0000000000000000e+000 (0) KKT[3][0][ 1, 2]=0.0000000000000000e+000 (1) KKT[3][0][ 1, 3]=0.0000000000000000e+000 (2) KKT[3][0][ 1, 4]=0.0000000000000000e+000 (3) KKT[3][0][ 1, 5]=0.0000000000000000e+000 (4) KKT[3][0][ 1, 6]=1.0000000000000000e+000 (5) KKT[3][0][ 2, 1]=1.0000000000000000e+000 (6) KKT[3][0][ 2, 2]=-1.0000000000000000e+000 (7) KKT[3][0][ 2, 3]=0.0000000000000000e+000 (8) KKT[3][0][ 2, 4]=0.0000000000000000e+000 (9) KKT[3][0][ 2, 5]=0.0000000000000000e+000 (10) KKT[3][0][ 2, 6]=1.0000000000000000e+000 (11) Component for row 3 and column 1: IdentityMatrix "KKT[3][1]" with 2 rows and columns and the factor -1.0000000000000000e+000. Component for row 3 and column 2: This component has not been set. Component for row 3 and column 3: DiagMatrix "KKT[3][3]" with 2 rows and columns, and with diagonal elements: DenseVector "KKT[3][3]" with 2 elements: Homogeneous vector, all elements have value -0.0000000000000000e+000 ******* KKT SYSTEM ******* (0) KKT[1][1] = 0.000000000000000e+000 (1) KKT[2][1] = 0.000000000000000e+000 (2) KKT[2][2] = 0.000000000000000e+000 (3) KKT[3][1] = 0.000000000000000e+000 (4) KKT[3][2] = 0.000000000000000e+000 (5) KKT[3][3] = 0.000000000000000e+000 (6) KKT[4][1] = 0.000000000000000e+000 (7) KKT[4][2] = 0.000000000000000e+000 (8) KKT[4][3] = 0.000000000000000e+000 (9) KKT[4][4] = 0.000000000000000e+000 (10) KKT[5][1] = 0.000000000000000e+000 (11) KKT[5][2] = 0.000000000000000e+000 (12) KKT[5][3] = 0.000000000000000e+000 (13) KKT[5][4] = 0.000000000000000e+000 (14) KKT[5][5] = 0.000000000000000e+000 (15) KKT[6][1] = 0.000000000000000e+000 (16) KKT[6][2] = 0.000000000000000e+000 (17) KKT[6][3] = 0.000000000000000e+000 (18) KKT[6][4] = 0.000000000000000e+000 (19) KKT[6][5] = 0.000000000000000e+000 (20) KKT[6][6] = 0.000000000000000e+000 (21) KKT[-842150450][-842150450] = 0.000000000000000e+000 (22) KKT[-842150450][-842150450] = 0.000000000000000e+000 (23) KKT[-842150450][-842150450] = 0.000000000000000e+000 (24) KKT[-842150450][-842150450] = 0.000000000000000e+000 (25) KKT[-842150450][-842150450] = 0.000000000000000e+000 (26) KKT[-842150450][-842150450] = 0.000000000000000e+000 (27) KKT[-842150450][-842150450] = 0.000000000000000e+000 (28) KKT[-842150450][-842150450] = 0.000000000000000e+000 (29) KKT[-842150450][-842150450] = 0.000000000000000e+000 (30) KKT[-842150450][-842150450] = 0.000000000000000e+000 (31) KKT[-842150450][-842150450] = 0.000000000000000e+000 (32) KKT[-842150450][-842150450] = 0.000000000000000e+000 (33) KKT[-842150450][-842150450] = 0.000000000000000e+000 (34) KKT[-842150450][-842150450] = 0.000000000000000e+000 (35) KKT[-842150450][-842150450] = 0.000000000000000e+000 (36) KKT[1][1] = 1.000000000000000e+000 (37) KKT[2][2] = 1.000000000000000e+000 (38) KKT[3][3] = 1.000000000000000e+000 (39) KKT[4][4] = 1.000000000000000e+000 (40) KKT[5][5] = 1.000000000000000e+000 (41) KKT[6][6] = 1.000000000000000e+000 (42) KKT[7][7] = 1.000000000000000e+000 (43) KKT[8][8] = 1.000000000000000e+000 (44) KKT[9][1] = 0.000000000000000e+000 (45) KKT[9][2] = 0.000000000000000e+000 (46) KKT[9][3] = 0.000000000000000e+000 (47) KKT[9][4] = 0.000000000000000e+000 (48) KKT[9][5] = 0.000000000000000e+000 (49) KKT[9][6] = 1.000000000000000e+000 (50) KKT[10][1] = 1.000000000000000e+000 (51) KKT[10][2] = -1.000000000000000e+000 (52) KKT[10][3] = 0.000000000000000e+000 (53) KKT[10][4] = 0.000000000000000e+000 (54) KKT[10][5] = 0.000000000000000e+000 (55) KKT[10][6] = 1.000000000000000e+000 (56) KKT[9][7] = -1.000000000000000e+000 (57) KKT[10][8] = -1.000000000000000e+000 (58) KKT[9][9] = -0.000000000000000e+000 (59) KKT[10][10] = -0.000000000000000e+000 Right hand side 0 in TSymLinearSolver: Trhs[ 0, 0] = 2.0000000000000000e+000 Trhs[ 0, 1] = -2.0000000000000000e+000 Trhs[ 0, 2] = -0.0000000000000000e+000 Trhs[ 0, 3] = -0.0000000000000000e+000 Trhs[ 0, 4] = -0.0000000000000000e+000 Trhs[ 0, 5] = 2.0000000000000000e+000 Trhs[ 0, 6] = 1.0000000000000000e+000 Trhs[ 0, 7] = 1.0000000000000000e+000 Trhs[ 0, 8] = 0.0000000000000000e+000 Trhs[ 0, 9] = 0.0000000000000000e+000 Calling MUMPS-1 for symbolic factorization at cpu time 4.624 (wall 0.097).