Routine |
Mark of Introduction |
Purpose |
|---|---|---|
| e04ab | 27 | nagad_opt_one_var_func Minimizes a function of one variable, using function values only |
| e04dg | 26.2 | nagad_opt_uncon_conjgrd_comp Unconstrained minimum, preconditioned conjugate gradient algorithm, using first derivatives (comprehensive) |
| e04fc | 26.2 | nagad_opt_lsq_uncon_mod_func_comp (Second order AD) Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm, using function values only (comprehensive) |
| e04gb | 26.2 | nagad_opt_lsq_uncon_quasi_deriv_comp (symbolic adjoint strategy) (Second order AD) Unconstrained minimum of a sum of squares, combined Gauss–Newton and quasi-Newton algorithm, using first derivatives (comprehensive) |
| e04kf | 27.1 | nagad_opt_handle_solve_bounds_foas First-order active-set method for box constrained nonlinear optimization with low memory requirements |
| e04nc | 27.1 | nagad_opt_lsq_lincon_solve Linear programming (LP) convex quadratic programming (QP) or linearly-constrained linear least squares problem, dense |
| e04nd | 27.1 | nagad_opt_lsq_lincon_option_file Supply optional parameter values for e04nc from external file |
| e04ne | 27.1 | nagad_opt_lsq_lincon_option_string Supply optional parameter values to e04nc from a character string |
| e04ra | 27.1 | nagad_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) |
| e04ta | 27.1 | nagad_opt_handle_add_vars Add new variables to a problem initialized by e04ra |
| e04tb | 27.1 | nagad_opt_handle_enable Enable components of the model which were previously disabled by e04tc |
| e04tc | 27.1 | nagad_opt_handle_disable Disable components in the problem initialized by e04ra |
| e04td | 27.1 | nagad_opt_handle_set_bound Set or modify a bound for an existing constraint (a simple bound, a linear or nonlinear constraint) of a problem initialized by e04ra |
| e04te | 27.1 | nagad_opt_handle_set_linobj_coeff Set or modify a single coefficient in the linear objective function of a problem initialized by e04ra |
| e04tj | 27.1 | nagad_opt_handle_set_linconstr_coeff Set or modify a single coefficient in a linear constraint of a problem initialized by e04ra |
| e04uc | 27.1 | nagad_opt_nlp1_solve Nonlinear programming (NLP), dense, active-set SQP method, using function values and optionally first derivatives, recommended |
| e04ud | 27.1 | nagad_opt_nlp1_option_file Supply optional parameter values for e04uc or e04uf from external file |
| e04ue | 27.1 | nagad_opt_nlp1_option_string Supply optional parameter values to e04uc or e04uf from a character string |
| e04ur | 27.3 | nagad_opt_lsq_gencon_deriv_option_string (Second order AD) Supply optional parameter values to e04us from a character string |
| e04us | 27 | nagad_opt_lsq_gencon_deriv (Second order AD) Minimum of a sum of squares, nonlinear constraints, dense, active-set SQP method, using function values and optionally first derivatives |
| e04wb | 27.1 | nagad_opt_nlp1_init (Second order AD) Initialization routine for e04dg, e04mf, e04nc, e04nf, e04nk, e04uc, e04uf, e04ug, e04us |