nlmixr2auto (version 1.0.0)

ga.operator: Genetic algorithm operator for model selection

Description

Run a genetic algorithm to search for an optimal PK model structure within a predefined search space using nlmixr2-based model fitting and penalties.

Usage

ga.operator(
  dat,
  param_table = NULL,
  search.space = c("ivbase", "oralbase"),
  no.cores = NULL,
  ga.control = gaControl(),
  penalty.control = penaltyControl(),
  precomputed_results_file = NULL,
  foldername = NULL,
  filename = "test",
  seed = 1234,
  .modEnv = NULL,
  verbose = TRUE,
  ...
)

Value

An object of class "gaOperatorResult" containing:

• Final Selected Code: data frame with the best binary encoding.

• Final Selected Model Name: model identifier for the best encoding.

• Model Run History: data frame of fitted models and fitness values.

• Selection History: list of per-generation results.

Arguments

dat

A data frame containing pharmacokinetic data in standard nlmixr2 format, including "ID", "TIME", "EVID", and "DV", and may include additional columns.

param_table

Optional data frame of initial parameter estimates. If NULL, the table is generated by auto_param_table().

search.space

Character, one of "ivbase" or "oralbase". Default is "ivbase".

no.cores

Integer. Number of CPU cores to use. If NULL, uses rxode2::getRxThreads().

ga.control

A list of GA control parameters, generated by gaControl(). Includes:

• npop - number of individuals (chromosomes) per generation.

• niter - maximum number of generations.

• pcross - crossover probability.

• pmut - per-bit mutation probability.

• diff_tol - significance difference threshold used for ranking.

• nls - frequency (in generations) of running local exhaustive search around the best current model.

penalty.control

A list of penalty control parameters defined by penaltyControl(), specifying penalty values used for model diagnostics during fitness evaluation.

precomputed_results_file

Optional path to a CSV file of previously computed model results used for caching.

foldername

Character string specifying the folder name for storing intermediate results. If NULL (default), tempdir() is used for temporary storage. If specified, a cache directory is created in the current working directory.

filename

Optional character string used as a prefix for output files. Defaults to "test".

seed

Integer. Random seed controlling the random sampling steps of the genetic algorithm operator for reproducible runs. Default is 1234.

.modEnv

Optional environment used to store run state and cached results. If NULL, a new environment is created.

verbose

Logical. If TRUE, print progress messages.

...

Additional arguments passed to mod.run().

Author

Zhonghui Huang

Details

The algorithm evolves a population of binary-encoded candidate models over multiple generations using tournament selection, crossover, mutation, and local search. Candidate encodings are validated and then evaluated by fitting models and applying user-defined penalties. The best individual is carried forward to the next generation.

See Also

mod.run, gaControl, penaltyControl, auto_param_table, spaceConfig, create.pop, validStringbinary, decodeBinary, parseName, rank_new, runlocal, ga.sel.tournament, ga.crossover, ga.mutation

Examples

# \donttest{
# Example usage with phenotype dataset
outs <- ga.operator(
  dat = pheno_sd,
  param_table = NULL,
  search.space = "ivbase",
  ga.control = gaControl(),
  saem.control = nlmixr2est::saemControl(
    seed = 1234,
    nBurn = 200,
    nEm   = 300,
    logLik = TRUE
  )
)
print(outs)
# }