Function |
Mark of Introduction |
Purpose |
|---|---|---|
| e04abc
Example Text |
5 | nag_opt_one_var_func Minimizes a function of one variable, using function values only |
| e04bbc
Example Text |
5 | nag_opt_one_var_deriv Minimizes a function of one variable, requires first derivatives |
| e04cbc
Example Text Example Plot |
9 | nag_opt_uncon_simplex Unconstrained minimum, Nelder–Mead simplex algorithm, using function values only |
| e04dgc
Example Text Example Options |
2 (Deprecated) | nag_opt_uncon_conjgrd_comp Unconstrained minimization using conjugate gradients |
| e04fcc
Example Text Example Options |
2 | nag_opt_lsq_uncon_mod_func_comp Unconstrained nonlinear least squares (no derivatives required) |
| e04ffc
Example Text |
26.1 | nag_opt_handle_solve_dfls Derivative-free (DFO) solver for a nonlinear least squares objective function with bounded variables |
| e04fgc
Example Text |
27 | nag_opt_handle_solve_dfls_rcomm Reverse communication derivative-free (DFO) solver for a nonlinear least squares objective function with bounded variables |
| e04gbc
Example Text Example Options |
2 | nag_opt_lsq_uncon_quasi_deriv_comp Unconstrained nonlinear least squares (first derivatives required) |
| e04hcc
Example Text |
2 | nag_opt_check_deriv Derivative checker |
| e04hdc
Example Text |
5 | nag_opt_check_deriv2 Checks second derivatives of a user-defined function |
| e04jcc
Example Text |
23 (Deprecated) | nag_opt_bounds_bobyqa_func Bound constrained minimum, model-based algorithm, using function values only |
| e04jdc
Example Text |
27 | nag_opt_handle_solve_dfno Direct communication derivative-free (DFO) solver for a nonlinear objective function with bounded variables |
| e04jec
Example Text |
27 | nag_opt_handle_solve_dfno_rcomm Reverse communication derivative-free (DFO) solver for a nonlinear objective function with bounded variables |
| e04kbc
Example Text Example Options |
2 | nag_opt_bounds_deriv Bound constrained nonlinear minimization (first derivatives required) |
| e04kfc
Example Text |
27 | nag_opt_handle_solve_bounds_foas First order active-set method for box constrained nonlinear optimization with low memory requirements |
| e04lbc
Example Text Example Options |
5 | nag_opt_bounds_mod_deriv2_comp Solves bound constrained problems (first and second derivatives required) |
| e04mfc
Example Text Example Options |
2 | nag_opt_lp_solve Linear programming |
| e04mtc
Example Text Example Data |
26.1 | nag_opt_handle_solve_lp_ipm Linear programming (LP), sparse, interior point method (IPM) |
| e04mwc
Example Text Example Data |
26 | nag_opt_miqp_mps_write Write MPS data file defining LP, QP, MILP or MIQP problem |
| e04mxc
Example Text Example Options |
24 | nag_opt_miqp_mps_read Read MPS data file defining LP, QP, MILP or MIQP problem |
| e04myc | 5 | nag_opt_sparse_mps_free Free memory allocated by e04mzc |
| e04mzc
Example Text Example Data |
5 | nag_opt_qpconvex1_sparse_mps Read MPSX data for sparse LP or QP problem from a file |
| e04ncc
Example Text Example Data |
5 | nag_opt_lsq_lincon_solve Solves linear least squares and convex quadratic programming problems (non-sparse) |
| e04nfc
Example Text Example Options |
2 | nag_opt_qp_dense_solve Quadratic programming |
| e04nkc
Example Text Example Data |
5 | nag_opt_qpconvex1_sparse_solve Solves sparse linear programming or convex quadratic programming problems |
| e04npc | 8 | nag_opt_qpconvex2_sparse_init Initialization function for e04nqc |
| e04nqc
Example Text Example Data |
8 | nag_opt_qpconvex2_sparse_solve Linear programming (LP) or convex quadratic programming (QP), sparse, active-set method, recommended |
| e04nrc
Example Text |
8 | nag_opt_qpconvex2_sparse_option_file Supply optional parameter values for e04nqc from external file |
| e04nsc | 8 | nag_opt_qpconvex2_sparse_option_string Set a single option for e04nqc from a character string |
| e04ntc | 8 | nag_opt_qpconvex2_sparse_option_integer_set Set a single option for e04nqc from an integer argument |
| e04nuc | 8 | nag_opt_qpconvex2_sparse_option_double_set Set a single option for e04nqc from a real argument |
| e04nxc | 8 | nag_opt_qpconvex2_sparse_option_integer_get Get the setting of an integer valued option of e04nqc |
| e04nyc | 8 | nag_opt_qpconvex2_sparse_option_double_get Get the setting of a real valued option of e04nqc |
| e04pcc
Example Text Example Data |
24 | nag_opt_bnd_lin_lsq Computes the least squares solution to a set of linear equations subject to fixed upper and lower bounds on the variables. An option is provided to return a minimal length solution if a solution is not unique |
| e04ptc
Example Text Example Data |
27 | nag_opt_handle_solve_socp_ipm Solve second-order cone programming (SOCP) and other convex related problems, such as, quadratically constrained quadratic programming (QCQP), quadratic programming (QP), sparse, interior point method (IPM) |
| e04rac | 26 | nag_opt_handle_init Initialization of a handle for the NAG optimization modelling suite for problems, such as, linear programming (LP), quadratic programming (QP), nonlinear programming (NLP), least squares (LSQ) problems, linear semidefinite programming (SDP) or SDP with bilinear matrix inequalities (BMI-SDP) |
| e04rbc
Example Text Example Data |
27 | nag_opt_handle_set_group Define a set of variables which form a second-order cone to a problem initialized by e04rac |
| e04rdc
Example Text Example Options |
26 | nag_opt_sdp_read_sdpa A reader of sparse SDPA data files for linear SDP problems |
| e04rec | 26 | nag_opt_handle_set_linobj Define a linear objective function to a problem initialized by e04rac |
| e04rfc
Example Text Example Data |
26 | nag_opt_handle_set_quadobj Define a linear or a quadratic objective function to a problem initialized by e04rac |
| e04rgc | 26 | nag_opt_handle_set_nlnobj Define a nonlinear objective function to a problem initialized by e04rac |
| e04rhc
Example Text Example Data |
26 | nag_opt_handle_set_simplebounds Define bounds of variables of a problem initialized by e04rac |
| e04rjc
Example Text Example Options |
26 | nag_opt_handle_set_linconstr Define a block of linear constraints to a problem initialized by e04rac |
| e04rkc | 26 | nag_opt_handle_set_nlnconstr Define a block of nonlinear constraints to a problem initialized by e04rac |
| e04rlc | 26 | nag_opt_handle_set_nlnhess Define a structure of Hessian of the objective, constraints or the Lagrangian to a problem initialized by e04rac |
| e04rmc
Example Text |
26.1 | nag_opt_handle_set_nlnls Define a nonlinear least squares objective function for a problem initialized by e04rac |
| e04rnc
Example Text Example Data |
26 | nag_opt_handle_set_linmatineq Add one or more linear matrix inequality constraints to a problem initialized by e04rac |
| e04rpc
Example Text Example Data |
26 | nag_opt_handle_set_quadmatineq Define bilinear matrix terms to a problem initialized by e04rac |
| e04rxc
Example Text Example Data |
26.1 | nag_opt_handle_set_get_real Insert or extract data relating to a problem initialized by e04rac |
| e04ryc
Example Text |
26 | nag_opt_handle_print Print information about a problem handle initialized by e04rac |
| e04rzc | 26 | nag_opt_handle_free Destroy the problem handle initialized by e04rac and deallocate all the memory used |
| e04sac
Example Text Example Options |
27 | nag_opt_handle_read_file Load a problem from a file to a new handle for the NAG optimization modelling suite; supported formats: extended MPS, SDPA |
| e04stc
Example Text |
26 | nag_opt_handle_solve_ipopt Run an interior point solver on a sparse nonlinear programming problem (NLP) initialized by e04rac and defined by other functions from the suite |
| e04svc
Example Text Example Data |
26 | nag_opt_handle_solve_pennon Run the Pennon solver on a compatible problem initialized by e04rac and defined by other functions from the suite, such as, semidefinite programming (SDP) and SDP with bilinear matrix inequalities (BMI) |
| e04ucc
Example Text Example Options |
4 | nag_opt_nlp1_solve Minimization with nonlinear constraints using a sequential QP method |
| e04udc
Example Text |
23 | nag_opt_nlp1_option_file Supply optional parameter values for e04ucc or e04ufc from external file |
| e04uec | 23 | nag_opt_nlp1_option_string Supply optional parameter values to e04ucc or e04ufc from a character string |
| e04ufc
Example Text Example Data |
23 | nag_opt_nlp1_rcomm Nonlinear programming (NLP), dense, active-set, SQP method, using function values and optionally first derivatives (reverse communication, comprehensive) |
| e04ugc
Example Text Example Options |
6 | nag_opt_nlp1_sparse_solve NLP problem (sparse) |
| e04unc
Example Text Example Data |
5 | nag_opt_nlin_lsq Solves nonlinear least squares problems using the sequential QP method |
| e04vgc | 8 | nag_opt_nlp2_sparse_init Initialization function for e04vhc |
| e04vhc
Example Text Example Data |
8 | nag_opt_nlp2_sparse_solve Nonlinear programming (NLP), sparse, active-set SQP method, using function values and optionally first derivatives, recommended |
| e04vjc
Example Text Example Data |
8 | nag_opt_nlp2_sparse_jacobian Determine the pattern of nonzeros in the Jacobian matrix for e04vhc |
| e04vkc
Example Text |
8 | nag_opt_nlp2_sparse_option_file Supply optional parameter values for e04vhc from external file |
| e04vlc | 8 | nag_opt_nlp2_sparse_option_string Set a single option for e04vhc from a character string |
| e04vmc | 8 | nag_opt_nlp2_sparse_option_integer_set Set a single option for e04vhc from an integer argument |
| e04vnc | 8 | nag_opt_nlp2_sparse_option_double_set Set a single option for e04vhc from a real argument |
| e04vrc | 8 | nag_opt_nlp2_sparse_option_integer_get Get the setting of an integer valued option of e04vhc |
| e04vsc | 8 | nag_opt_nlp2_sparse_option_double_get Get the setting of a real valued option of e04vhc |
| e04wbc | 23 | nag_opt_nlp1_init Initialization function for e04ufc |
| e04wcc | 8 | nag_opt_nlp2_init Initialization function for e04wdc |
| e04wdc
Example Text Example Data |
8 | nag_opt_nlp2_solve Nonlinear programming (NLP), dense, active-set SQP method, using function values and optionally first derivatives |
| e04wec
Example Text |
8 | nag_opt_nlp2_option_file Supply optional parameter values for e04wdc from external file |
| e04wfc | 8 | nag_opt_nlp2_option_string Set a single option for e04wdc from a character string |
| e04wgc | 8 | nag_opt_nlp2_option_integer_set Set a single option for e04wdc from an integer argument |
| e04whc | 8 | nag_opt_nlp2_option_double_set Set a single option for e04wdc from a real argument |
| e04wkc | 8 | nag_opt_nlp2_option_integer_get Get the setting of an integer valued option of e04wdc |
| e04wlc | 8 | nag_opt_nlp2_option_double_get Get the setting of a real valued option of e04wdc |
| e04xac
Example Text |
5 | nag_opt_estimate_deriv Computes an approximation to the gradient vector and/or the Hessian matrix |
| e04xxc | 2 | nag_opt_init Initialization function for option setting |
| e04xyc | 2 | nag_opt_read Read options from a text file |
| e04xzc | 2 | nag_opt_free Memory freeing function for use with option setting |
| e04yac
Example Text Example Data |
2 | nag_opt_lsq_check_deriv Least squares derivative checker for use with e04gbc |
| e04ycc
Example Text Example Data |
2 | nag_opt_lsq_uncon_covariance Covariance matrix for nonlinear least squares |
| e04zmc | 26 | nag_opt_handle_opt_set Option setting routine for the solvers from the NAG optimization modelling suite |
| e04znc | 26 | nag_opt_handle_opt_get Option getting routine for the solvers from the NAG optimization modelling suite |
| e04zpc | 26 | nag_opt_handle_opt_set_file Option setting routine for the solvers from the NAG optimization modelling suite from external file |