qpb_control_type structure#
#include <galahad_qpb.h> struct qpb_control_type { // components bool f_indexing; ipc_ error; ipc_ out; ipc_ print_level; ipc_ start_print; ipc_ stop_print; ipc_ maxit; ipc_ itref_max; ipc_ cg_maxit; ipc_ indicator_type; ipc_ restore_problem; ipc_ extrapolate; ipc_ path_history; ipc_ factor; ipc_ max_col; ipc_ indmin; ipc_ valmin; ipc_ infeas_max; ipc_ precon; ipc_ nsemib; ipc_ path_derivatives; ipc_ fit_order; ipc_ sif_file_device; rpc_ infinity; rpc_ stop_p; rpc_ stop_d; rpc_ stop_c; rpc_ theta_d; rpc_ theta_c; rpc_ beta; rpc_ prfeas; rpc_ dufeas; rpc_ muzero; rpc_ reduce_infeas; rpc_ obj_unbounded; rpc_ pivot_tol; rpc_ pivot_tol_for_dependencies; rpc_ zero_pivot; rpc_ identical_bounds_tol; rpc_ inner_stop_relative; rpc_ inner_stop_absolute; rpc_ initial_radius; rpc_ mu_min; rpc_ inner_fraction_opt; rpc_ indicator_tol_p; rpc_ indicator_tol_pd; rpc_ indicator_tol_tapia; rpc_ cpu_time_limit; rpc_ clock_time_limit; bool remove_dependencies; bool treat_zero_bounds_as_general; bool center; bool primal; bool puiseux; bool feasol; bool array_syntax_worse_than_do_loop; bool space_critical; bool deallocate_error_fatal; bool generate_sif_file; char sif_file_name[31]; char prefix[31]; struct lsqp_control_type lsqp_control; struct fdc_control_type fdc_control; struct sbls_control_type sbls_control; struct gltr_control_type gltr_control; struct fit_control_type fit_control; };
detailed documentation#
control derived type as a C struct
components#
bool f_indexing
use C or Fortran sparse matrix indexing
ipc_ error
error and warning diagnostics occur on stream error
ipc_ out
general output occurs on stream out
ipc_ print_level
the level of output required is specified by print_level
ipc_ start_print
any printing will start on this iteration
ipc_ stop_print
any printing will stop on this iteration
ipc_ maxit
at most maxit inner iterations are allowed
ipc_ itref_max
the maximum number of iterative refinements allowed
ipc_ cg_maxit
the maximum number of CG iterations allowed. If cg_maxit < 0, this number will be reset to the dimension of the system + 1
ipc_ indicator_type
specifies the type of indicator function used. Pssible values are
1 primal indicator: constraint active <=> distance to nearest bound <= .indicator_p_tol
2 primal-dual indicator: constraint active <=> distance to nearest bound <= .indicator_tol_pd * size of corresponding multiplier
3 primal-dual indicator: constraint active <=> distance to nearest bound <= .indicator_tol_tapia * distance to same bound at previous iteration
ipc_ restore_problem
indicate whether and how much of the input problem should be restored on output. Possible values are
0 nothing restored
1 scalar and vector parameters
2 all parameters
ipc_ extrapolate
should extrapolation be used to track the central path? Possible values
0 never
1 after the final major iteration
2 at each major iteration
ipc_ path_history
the maximum number of previous path points to use when fitting the data
ipc_ factor
the factorization to be used. Possible values are
0 automatic
1 Schur-complement factorization
2 augmented-system factorization
ipc_ max_col
the maximum number of nonzeros in a column of A which is permitted with the Schur-complement factorization
ipc_ indmin
an initial guess as to the integer workspace required by SBLS
ipc_ valmin
an initial guess as to the real workspace required by SBLS
ipc_ infeas_max
the number of iterations for which the overall infeasibility of the problem is not reduced by at least a factor .reduce_infeas before the problem is flagged as infeasible (see reduce_infeas)
ipc_ precon
the preconditioner to be used for the CG is defined by precon. Possible values are
0 automatic
1 no preconditioner, i.e, the identity within full factorization
2 full factorization
3 band within full factorization
4 diagonal using the barrier terms within full factorization
ipc_ nsemib
the semi-bandwidth of a band preconditioner, if appropriate
ipc_ path_derivatives
the maximum order of path derivative to use
ipc_ fit_order
the order of (Puiseux) series to fit to the path data: <=0 to fit all data
ipc_ sif_file_device
specifies the unit number to write generated SIF file describing the current problem
rpc_ infinity
any bound larger than infinity in modulus will be regarded as infinite
rpc_ stop_p
the required accuracy for the primal infeasibility
rpc_ stop_d
the required accuracy for the dual infeasibility
rpc_ stop_c
the required accuracy for the complementarity
rpc_ theta_d
tolerances used to terminate the inner iteration (for given mu): dual feasibility <= MAX( theta_d * mu ** beta, 0.99 * stop_d ) complementarity <= MAX( theta_c * mu ** beta, 0.99 * stop_d )
rpc_ theta_c
see theta_d
rpc_ beta
see theta_d
rpc_ prfeas
initial primal variables will not be closer than prfeas from their bound
rpc_ dufeas
initial dual variables will not be closer than dufeas from their bounds
rpc_ muzero
the initial value of the barrier parameter. If muzero is not positive, it will be reset to an appropriate value
rpc_ reduce_infeas
if the overall infeasibility of the problem is not reduced by at least a factor reduce_infeas over .infeas_max iterations, the problem is flagged as infeasible (see infeas_max)
rpc_ obj_unbounded
if the objective function value is smaller than obj_unbounded, it will be flagged as unbounded from below.
rpc_ pivot_tol
the threshold pivot used by the matrix factorization. See the documentation for SBLS for details
rpc_ pivot_tol_for_dependencies
the threshold pivot used by the matrix factorization when attempting to detect linearly dependent constraints. See the documentation for FDC for details
rpc_ zero_pivot
any pivots smaller than zero_pivot in absolute value will be regarded to zero when attempting to detect linearly dependent constraints
rpc_ identical_bounds_tol
any pair of constraint bounds (c_l,c_u) or (x_l,x_u) that are closer than identical_bounds_tol will be reset to the average of their values
rpc_ inner_stop_relative
the search direction is considered as an acceptable approximation to the minimizer of the model if the gradient of the model in the preconditioning(inverse) norm is less than max( inner_stop_relative * initial preconditioning(inverse) gradient norm, inner_stop_absolute )
rpc_ inner_stop_absolute
see inner_stop_relative
rpc_ initial_radius
the initial trust-region radius
rpc_ mu_min
start terminal extrapolation when mu reaches mu_min
rpc_ inner_fraction_opt
a search direction which gives at least inner_fraction_opt times the optimal model decrease will be found
rpc_ indicator_tol_p
if .indicator_type = 1, a constraint/bound will be deemed to be active <=> distance to nearest bound <= .indicator_p_tol
rpc_ indicator_tol_pd
if .indicator_type = 2, a constraint/bound will be deemed to be active <=> distance to nearest bound <= .indicator_tol_pd * size of corresponding multiplier
rpc_ indicator_tol_tapia
if .indicator_type = 3, a constraint/bound will be deemed to be active <=> distance to nearest bound <= .indicator_tol_tapia * distance to same bound at previous iteration
rpc_ cpu_time_limit
the maximum CPU time allowed (-ve means infinite)
rpc_ clock_time_limit
the maximum elapsed clock time allowed (-ve means infinite)
bool remove_dependencies
the equality constraints will be preprocessed to remove any linear dependencies if true
bool treat_zero_bounds_as_general
any problem bound with the value zero will be treated as if it were a general value if true
bool center
if .center is true, the algorithm will use the analytic center of the feasible set as its initial feasible point. Otherwise, a feasible point as close as possible to the initial point will be used. We recommend using the analytic center
bool primal
if .primal, is true, a primal barrier method will be used in place of t primal-dual method
bool puiseux
If extrapolation is to be used, decide between Puiseux and Taylor series.
bool feasol
if .feasol is true, the final solution obtained will be perturbed so that variables close to their bounds are moved onto these bounds
bool array_syntax_worse_than_do_loop
if .array_syntax_worse_than_do_loop is true, f77-style do loops will be used rather than f90-style array syntax for vector operations
bool space_critical
if .space_critical true, every effort will be made to use as little space as possible. This may result in longer computation time
bool deallocate_error_fatal
if .deallocate_error_fatal is true, any array/pointer deallocation error will terminate execution. Otherwise, computation will continue
bool generate_sif_file
if .generate_sif_file is .true. if a SIF file describing the current problem is to be generated
char sif_file_name[31]
name of generated SIF file containing input problem
char prefix[31]
all output lines will be prefixed by .prefix(2:LEN(TRIM(.prefix))-1) where .prefix contains the required string enclosed in quotes, e.g. “string” or ‘string’
struct lsqp_control_type lsqp_control
control parameters for LSQP
struct fdc_control_type fdc_control
control parameters for FDC
struct sbls_control_type sbls_control
control parameters for SBLS
struct gltr_control_type gltr_control
control parameters for GLTR
struct fit_control_type fit_control
control parameters for FIT