lsqp_control_type structure#
#include <galahad_lsqp.h> struct lsqp_control_type { // components bool f_indexing; ipc_ error; ipc_ out; ipc_ print_level; ipc_ start_print; ipc_ stop_print; ipc_ maxit; ipc_ factor; ipc_ max_col; ipc_ indmin; ipc_ valmin; ipc_ itref_max; ipc_ infeas_max; ipc_ muzero_fixed; ipc_ restore_problem; ipc_ indicator_type; ipc_ extrapolate; ipc_ path_history; ipc_ path_derivatives; ipc_ fit_order; ipc_ sif_file_device; rpc_ infinity; rpc_ stop_p; rpc_ stop_d; rpc_ stop_c; rpc_ prfeas; rpc_ dufeas; rpc_ muzero; rpc_ reduce_infeas; rpc_ potential_unbounded; rpc_ pivot_tol; rpc_ pivot_tol_for_dependencies; rpc_ zero_pivot; rpc_ identical_bounds_tol; rpc_ mu_min; 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 just_feasible; bool getdua; bool puiseux; bool feasol; bool balance_initial_complentarity; bool use_corrector; 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 fdc_control_type fdc_control; struct sbls_control_type sbls_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_ 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_ itref_max
the maximum number of iterative refinements allowed
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_ muzero_fixed
the initial value of the barrier parameter will not be changed for the first muzero_fixed iterations
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_ indicator_type
specifies the type of indicator function used. Possible values are
1 primal indicator: constraint active if and only if the distance to nearest bound \(\leq\).indicator_p_tol
2 primal-dual indicator: constraint active if and only if the distance to nearest bound \(\leq\).indicator_tol_pd \* size of corresponding multiplier
3 primal-dual indicator: constraint active if and only if the distance to the nearest bound \(\leq\).indicator_tol_tapia \* distance to same bound at previous iteration
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 (unused at present)
ipc_ path_history
the maximum number of previous path points to use when fitting the data (unused at present)
ipc_ path_derivatives
the maximum order of path derivative to use (unused at present)
ipc_ fit_order
the order of (Puiseux) series to fit to the path data: $
to fit all data (unused at present)
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_ prfeas
initial primal variables will not be closer than prfeas from their bounds
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_ potential_unbounded
if W=0 and the potential function value is smaller than potential_unbounded * number of one-sided bounds, the analytic center will be flagged as unbounded
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 SBLS 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 tha identical_bounds_tol will be reset to the average of their values
rpc_ mu_min
start terminal extrapolation when mu reaches mu_min
rpc_ indicator_tol_p
if .indicator_type = 1, a constraint/bound will be deemed to be active if and only if the distance to nearest bound $ \(\leq\).indicator_p_tol
rpc_ indicator_tol_pd
if .indicator_type = 2, a constraint/bound will be deemed to be active if and only if the distance to nearest bound $ \(\leq\).indicator_tol_pd \* size of corresponding multiplier
rpc_ indicator_tol_tapia
if .indicator_type = 3, a constraint/bound will be deemed to be active if and only if the distance to nearest bound $ \(\leq\).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 just_feasible
if .just_feasible is true, the algorithm will stop as soon as a feasible point is found. Otherwise, the optimal solution to the problem will be found
bool getdua
if .getdua, is true, advanced initial values are obtained for the dual variables
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 tha variables close to their bounds are moved onto these bounds
bool balance_initial_complentarity
if .balance_initial_complentarity is true, the initial complemetarity is required to be balanced
bool use_corrector
if .use_corrector, a corrector step will be used
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 fdc_control_type fdc_control
control parameters for FDC
struct sbls_control_type sbls_control
control parameters for SBLS