defaultSAC: Default settings for the SACOBRA part of SACOBRA.
In SACOBRA: Self-Adjusting COBRA

Description Usage Arguments Details Value Author(s) See Also

Sets suitable defaults for the SACOBRA part of SACOBRA.
With the call setOpts(mySAC,defaultSAC()) it is possible to extend a partial list mySAC to a list containing all sac-elements (the missing ones are taken from defaultSAC()).

1	defaultSAC(DOSAC = 1)

DOSAC

[0|1|2] with default 1.
0: COBRA-R settings (turn off SACOBRA),
1: SACOBRA settings,
2: SACOBRA settings with fewer parameters and more online adjustements (aFF and aCF are done parameter free).

For backward compatibility, a logical DOSAC (deprecated) is mapped from FALSE to 0 and from TRUE to 1.

a list with the following elements (the values in parantheses [|] are the values for DOSAC=[0|1|2]):

`RS`	flag for random start algorithm `[FALSE\|TRUE\|TRUE]`
`RStype`	type of the function to calculate probability to start the internal optimizer with a random starting point`[NA\|"SIGMOID"\|"CONSTANT"]` (see function `RandomStart` in `SACOBRA.R`)
`RSmax`	maximum probability of a random start when `RStype=="SIGMOID"` (see `RandomStart` in `SACOBRA.R`). If `RStype=="CONSTANT"` then random start is done with a constant probability determined from mean(c(RSmax,RSmin)) `[NA\|0.3\|0.3]`
`RSmin`	minimum probability of a random start when `RStype=="SIGMOID"` (see `RandomStart` in `SACOBRA.R`) `[NA\|0.05\|0.05]`
`RSAUTO`	If TRUE then in every iteration where the fraction of feasible points in the population is smaller than 0.05, the RS probability is set to 0.3. `[FALSE\|FALSE\|TRUE]`
`aDRC`	flag for automatic DRC adjustment `[FALSE\|TRUE\|TRUE]`
`aFF`	flag for automatic objective function transformation `[FALSE\|TRUE\|TRUE]`
`aCF`	flag for automatic constraint function transformation `[FALSE\|TRUE\|TRUE]`
`TFRange`	threshold, if `FRange` is larger than `TFRange`, then apply automatic objective function transformation (see `plog`). `[Inf\|1e+05\|-1]`
`TGR`	threshold, if `GRatio` is larger than `TGR`, then apply automatic constraint function transformation. `GRatio` is the ratio "largest `GRange` / smallest `GRange`" where `GRange` is the min-max range of a specific constraint. If `TGR < 1`, then the transformation is always performed. `[Inf\|1e+03\|-1]`.
`Cs`	If `Cs` iterations in a row do not improve the ever-best feasible solution, then perform a random restart. `[10\|10\|10]`
`adaptivePLOG`	(experimental) flag for objective function transformation with `plog`, where the parameter `pShift` is adapted during iterations. `[FALSE\|FALSE\|FALSE]`
`onlinePLOG`	flag for online decision making wether use plog or not according to p-effect `plog`. `[FALSE\|FALSE\|TRUE]`
`pEffectInit`	Initial pEffect value when using onlinePLOG. If pEffectInit >= 2 then the initial model is built after plog transformation. `[NA\|NA\|2]`