scs_control_dflt
Tunable SCS solver parameters
Description
Allow the user to tune the parameters of the SCS solver procedure.
Usage
scs_control_dflt(
maxiter = 1e+05,
eps_rel = 1e-05,
eps_abs = 1e-05,
eps_infeas = 1e-07,
alpha_relax = 1.5,
rho_x = 1e-06,
scale = 0.1,
normalize = TRUE,
acceleration_lookback = 10,
acceleration_interval = 5,
adaptive_scale = TRUE,
adaptive_diag_scale = TRUE,
time_limit_secs = 60
)
Arguments
maxiter: positive integer, maximum number of iterations to run.eps_rel: positive numeric, relative feasibility tolerance.eps_abs: positive numeric, absolute feasibility tolerance.eps_infeas: positive numeric, infeasibility tolerance (primal and dual).alpha_relax: numeric value in (0, 2), douglas-Rachford relaxation parameter.rho_x: positive numeric, primal scale factor.scale: positive numeric, initial dual scale factor, updated ifadaptive_scaleisTRUE.normalize: logical, whether to perform heuristic data rescaling.acceleration_lookback: positive integer, relative amount of memory used for Anderson acceleration. More memory requires more time to compute but can give more reliable steps. Ifacceleration_lookback < 1, Anderson acceleration is disabled.acceleration_interval: positive integer, run Anderson acceleration everyacceleration_intervaliteration(s).adaptive_scale: logical, whether to heuristically adapt dual scale through the solve.adaptive_diag_scale: logical, whether to refine the metric R per row, using the primal residual profile. Requiresadaptive_scale(silently disabled without it).time_limit_secs: positive numeric, time limit for solve run in seconds (can be fractional). The value 0 is interpreted as no limit. The default is 60.
Seealso
https://www.cvxgrp.org/scs/api/settings
Value
A list with components:
- maxiter
- eps_rel
- eps_abs
- eps_infeas
- alpha_relax
- rho_x
- scale
- normalize
- acceleration_lookback
- acceleration_interval
- adaptive_scale
- adaptive_diag_scale
- time_limit_secs
with meanings as explained under ‘Arguments’.
Examples
## default tuning parameters
scs_control_dflt()