# NAG AD LibraryE04 (Opt)Minimizing or Maximizing a Function

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E04 (Opt) Chapter Introduction (FL Interface) – A description of the Chapter and an overview of the algorithms available.

Routine
Mark of
Introduction

Purpose
e04ab_a1w_f 27 nagf_opt_one_var_func_a1w
Minimizes a function of one variable, using function values only
e04dg_a1w_f 26.2 nagf_opt_uncon_conjgrd_comp_a1w
Unconstrained minimum, preconditioned conjugate gradient algorithm, using first derivatives (comprehensive)
e04fc_a1w_f 26.2 nagf_opt_lsq_uncon_mod_func_comp_a1w
Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm, using function values only (comprehensive)
e04gb_a1w_f 26.2 nagf_opt_lsq_uncon_quasi_deriv_comp_a1w (symbolic adjoint mode)
Unconstrained minimum of a sum of squares, combined Gauss–Newton and quasi-Newton algorithm, using first derivatives (comprehensive)
e04kf_a1w_f 27.1 nagf_opt_handle_solve_bounds_foas_a1w
First-order active-set method for box constrained nonlinear optimization with low memory requirements
e04nc_a1w_f 27.1 nagf_opt_lsq_lincon_solve_a1w
Linear programming (LP) convex quadratic programming (QP) or linearly-constrained linear least squares problem, dense
e04nd_a1w_f 27.1 nagf_opt_lsq_lincon_option_file_a1w
Supply optional parameter values for e04nc_a1w_f from external file
e04ne_a1w_f 27.1 nagf_opt_lsq_lincon_option_string_a1w
Supply optional parameter values to e04nc_a1w_f from a character string
e04ra_a1w_f 27.1 nagf_opt_handle_init_a1w
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)
Add new variables to a problem initialized by e04ra_a1w_f
e04tb_a1w_f 27.1 nagf_opt_handle_enable_a1w
Enable components of the model which were previously disabled by e04tc_a1w_f
e04tc_a1w_f 27.1 nagf_opt_handle_disable_a1w
Disable components in the problem initialized by e04ra_a1w_f
e04td_a1w_f 27.1 nagf_opt_handle_set_bound_a1w
Set or modify a bound for an existing constraint (a simple bound, a linear or nonlinear constraint) of a problem initialized by e04ra_a1w_f
e04te_a1w_f 27.1 nagf_opt_handle_set_linobj_coeff_a1w
Set or modify a single coefficient in the linear objective function of a problem initialized by e04ra_a1w_f
e04tj_a1w_f 27.1 nagf_opt_handle_set_linconstr_coeff_a1w
Set or modify a single coefficient in a linear constraint of a problem initialized by e04ra_a1w_f
e04uc_a1w_f 27.1 nagf_opt_nlp1_solve_a1w
Nonlinear programming (NLP), dense, active-set SQP method, using function values and optionally first derivatives, recommended
e04ud_a1w_f 27.1 nagf_opt_nlp1_option_file_a1w
Supply optional parameter values for e04uc_a1w_f or e04uf_a1w_f from external file
e04ue_a1w_f 27.1 nagf_opt_nlp1_option_string_a1w
Supply optional parameter values to e04uc_a1w_f or e04uf_a1w_f from a character string
e04us_a1w_f 27 nagf_opt_lsq_gencon_deriv_a1w
Minimum of a sum of squares, nonlinear constraints, dense, active-set SQP method, using function values and optionally first derivatives
e04wb_a1w_f 27.1 nagf_opt_nlp1_init_a1w
Initialization routine for e04dg_a1w_f, e04mf_a1w_f, e04nc_a1w_f, e04nf_a1w_f, e04nk_a1w_f, e04uc_a1w_f, e04uf_a1w_f, e04ug_a1w_f, e04us_a1w_f