For further details please consult the OSQP documentation: https://osqp.readthedocs.io/
1 2 3 4 5 6 7 8 | osqpSettings(rho = 0.1, sigma = 1e-06, max_iter = 4000L,
eps_abs = 0.001, eps_rel = 0.001, eps_prim_inf = 1e-04,
eps_dual_inf = 1e-04, alpha = 1.6,
linsys_solver = c(SUITESPARSE_LDL_SOLVER = 0L), delta = 1e-06,
polish = FALSE, polish_refine_iter = 3L, verbose = TRUE,
scaled_termination = FALSE, check_termination = 25L, warm_start = TRUE,
scaling = 10L, adaptive_rho = 1L, adaptive_rho_interval = 0L,
adaptive_rho_tolerance = 5, adaptive_rho_fraction = 0.4)
|
rho |
ADMM step rho |
sigma |
ADMM step sigma |
max_iter |
maximum iterations |
eps_abs |
absolute convergence tolerance |
eps_rel |
relative convergence tolerance |
eps_prim_inf |
primal infeasibility tolerance |
eps_dual_inf |
dual infeasibility tolerance |
alpha |
relaxation parameter |
linsys_solver |
which linear systems solver to use, 0=Suitesparse LDL, 1=MKL Pardiso |
delta |
regularization parameter for polish |
polish |
boolean, polish ADMM solution |
polish_refine_iter |
iterative refinement steps in polish |
verbose |
boolean, write out progres |
scaled_termination |
boolean, use scaled termination criteria |
check_termination |
integer, check termination interval. If 0, termination checking is disabled |
warm_start |
boolean, warm start |
scaling |
heuristic data scaling iterations. If 0, scaling disabled |
adaptive_rho |
cboolean, is rho step size adaptive? |
adaptive_rho_interval |
Number of iterations between rho adaptations rho. If 0, it is automatic |
adaptive_rho_tolerance |
Tolerance X for adapting rho. The new rho has to be X times larger or 1/X times smaller than the current one to trigger a new factorization |
adaptive_rho_fraction |
Interval for adapting rho (fraction of the setup time) |
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