e04 Chapter Introduction – a description of the Chapter and an overview of the algorithms available
| Function Name |
Mark of Introduction |
Purpose |
| e04abc
Example Text |
5 | nag_opt_one_var_no_deriv 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_simplex_easy Unconstrained minimum, Nelder–Mead simplex algorithm, using function values only |
| e04dgc
Example Text Example Options |
2 | nag_opt_conj_grad Unconstrained minimization using conjugate gradients |
| e04fcc
Example Text Example Options |
2 | nag_opt_lsq_no_deriv Unconstrained nonlinear least squares (no derivatives required) |
| e04gbc
Example Text Example Options |
2 | nag_opt_lsq_deriv Unconstrained nonlinear least squares (first derivatives required) |
| e04hcc
Example Text |
2 | nag_opt_check_deriv Derivative checker |
| e04hdc
Example Text |
5 | nag_opt_check_2nd_deriv Checks second derivatives of a user-defined function |
| e04jcc
Example Text |
23 | nag_opt_bounds_qa_no_deriv Bound constrained minimum, model-based algorithm, using function values only |
| e04kbc
Example Text Example Options |
2 | nag_opt_bounds_deriv Bound constrained nonlinear minimization (first derivatives required) |
| e04lbc
Example Text Example Options |
5 | nag_opt_bounds_2nd_deriv Solves bound constrained problems (first and second derivatives required) |
| e04mfc
Example Text Example Options |
2 | nag_opt_lp Linear programming |
| 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 nag_opt_sparse_mps_read (e04mzc) |
| e04mzc
Example Text Example Data |
5 | nag_opt_sparse_mps_read Read MPSX data for sparse LP or QP problem from a file |
| e04ncc
Example Text Example Data |
5 | nag_opt_lin_lsq Solves linear least squares and convex quadratic programming problems (non-sparse) |
| e04nfc
Example Text Example Options |
2 | nag_opt_qp Quadratic programming |
| e04nkc
Example Text Example Data |
5 | nag_opt_sparse_convex_qp Solves sparse linear programming or convex quadratic programming problems |
| e04npc | 8 | nag_opt_sparse_convex_qp_init Initialization function for nag_opt_sparse_convex_qp_solve (e04nqc) |
| e04nqc
Example Text Example Data |
8 | nag_opt_sparse_convex_qp_solve Linear programming (LP) or convex quadratic programming (QP), sparse, active-set method, recommended |
| e04nrc
Example Text |
8 | nag_opt_sparse_convex_qp_option_set_file Supply optional parameter values for nag_opt_sparse_convex_qp_solve (e04nqc) from external file |
| e04nsc | 8 | nag_opt_sparse_convex_qp_option_set_string Set a single option for nag_opt_sparse_convex_qp_solve (e04nqc) from a character string |
| e04ntc | 8 | nag_opt_sparse_convex_qp_option_set_integer Set a single option for nag_opt_sparse_convex_qp_solve (e04nqc) from an integer argument |
| e04nuc | 8 | nag_opt_sparse_convex_qp_option_set_double Set a single option for nag_opt_sparse_convex_qp_solve (e04nqc) from a real argument |
| e04nxc | 8 | nag_opt_sparse_convex_qp_option_get_integer Get the setting of an integer valued option of nag_opt_sparse_convex_qp_solve (e04nqc) |
| e04nyc | 8 | nag_opt_sparse_convex_qp_option_get_double Get the setting of a real valued option of nag_opt_sparse_convex_qp_solve (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 |
| e04rac | 26 | nag_opt_handle_init Initialization of a handle for the NAG optimization modelling suite for problems, such as, quadratic programming (QP), nonlinear programming (NLP), linear semidefinite programming (SDP) or SDP with bilinear matrix inequalities (BMI-SDP) |
| 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 nag_opt_handle_init (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 nag_opt_handle_init (e04rac) |
| e04rgc | 26 | nag_opt_handle_set_nlnobj Define a nonlinear objective function to a problem initialized by nag_opt_handle_init (e04rac) |
| e04rhc
Example Text Example Data |
26 | nag_opt_handle_set_simplebounds Define bounds of variables of a problem initialized by nag_opt_handle_init (e04rac) |
| e04rjc
Example Text Example Options |
26 | nag_opt_handle_set_linconstr Define a block of linear constraints to a problem initialized by nag_opt_handle_init (e04rac) |
| e04rkc | 26 | nag_opt_handle_set_nlnconstr Define a block of nonlinear constraints to a problem initialized by nag_opt_handle_init (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 nag_opt_handle_init (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 nag_opt_handle_init (e04rac) |
| e04rpc
Example Text Example Data |
26 | nag_opt_handle_set_quadmatineq Define bilinear matrix terms to a problem initialized by nag_opt_handle_init (e04rac) |
| e04ryc
Example Text |
26 | nag_opt_handle_print Print information about a problem handle initialized by nag_opt_handle_init (e04rac) |
| e04rzc | 26 | nag_opt_handle_free Destroy the problem handle initialized by nag_opt_handle_init (e04rac) and deallocate all the memory used |
| e04stc
Example Text |
26 | nag_opt_handle_solve_ipopt Run an interior point solver on a sparse nonlinear programming problem (NLP) initialized by nag_opt_handle_init (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 nag_opt_handle_init (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_nlp Minimization with nonlinear constraints using a sequential QP method |
| e04udc
Example Text |
23 | nag_opt_nlp_revcomm_option_set_file Supply optional parameter values for nag_opt_nlp (e04ucc) or nag_opt_nlp_revcomm (e04ufc) from external file |
| e04uec | 23 | nag_opt_nlp_revcomm_option_set_string Supply optional parameter values to nag_opt_nlp (e04ucc) or nag_opt_nlp_revcomm (e04ufc) from a character string |
| e04ufc
Example Text Example Data |
23 | nag_opt_nlp_revcomm 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_nlp_sparse 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_sparse_nlp_init Initialization function for nag_opt_sparse_nlp_solve (e04vhc) |
| e04vhc
Example Text Example Data |
8 | nag_opt_sparse_nlp_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_sparse_nlp_jacobian Determine the pattern of nonzeros in the Jacobian matrix for nag_opt_sparse_nlp_solve (e04vhc) |
| e04vkc
Example Text |
8 | nag_opt_sparse_nlp_option_set_file Supply optional parameter values for nag_opt_sparse_nlp_solve (e04vhc) from external file |
| e04vlc | 8 | nag_opt_sparse_nlp_option_set_string Set a single option for nag_opt_sparse_nlp_solve (e04vhc) from a character string |
| e04vmc | 8 | nag_opt_sparse_nlp_option_set_integer Set a single option for nag_opt_sparse_nlp_solve (e04vhc) from an integer argument |
| e04vnc | 8 | nag_opt_sparse_nlp_option_set_double Set a single option for nag_opt_sparse_nlp_solve (e04vhc) from a real argument |
| e04vrc | 8 | nag_opt_sparse_nlp_option_get_integer Get the setting of an integer valued option of nag_opt_sparse_nlp_solve (e04vhc) |
| e04vsc | 8 | nag_opt_sparse_nlp_option_get_double Get the setting of a real valued option of nag_opt_sparse_nlp_solve (e04vhc) |
| e04wbc | 23 | nag_opt_nlp_revcomm_init Initialization function for nag_opt_nlp_revcomm (e04ufc) |
| e04wcc | 8 | nag_opt_nlp_init Initialization function for nag_opt_nlp_solve (e04wdc) |
| e04wdc
Example Text Example Data |
8 | nag_opt_nlp_solve Nonlinear programming (NLP), dense, active-set SQP method, using function values and optionally first derivatives |
| e04wec
Example Text |
8 | nag_opt_nlp_option_set_file Supply optional parameter values for nag_opt_nlp_solve (e04wdc) from external file |
| e04wfc | 8 | nag_opt_nlp_option_set_string Set a single option for nag_opt_nlp_solve (e04wdc) from a character string |
| e04wgc | 8 | nag_opt_nlp_option_set_integer Set a single option for nag_opt_nlp_solve (e04wdc) from an integer argument |
| e04whc | 8 | nag_opt_nlp_option_set_double Set a single option for nag_opt_nlp_solve (e04wdc) from a real argument |
| e04wkc | 8 | nag_opt_nlp_option_get_integer Get the setting of an integer valued option of nag_opt_nlp_solve (e04wdc) |
| e04wlc | 8 | nag_opt_nlp_option_get_double Get the setting of a real valued option of nag_opt_nlp_solve (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 nag_opt_lsq_deriv (e04gbc) |
| e04ycc
Example Text Example Data |
2 | nag_opt_lsq_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 |