Add settings — add_settings • restoptr

Add settings to a restoration problem (restopt_problem()) object to customize the optimization procedure.

Usage

add_settings(
  problem,
  precision = 4,
  time_limit = 0,
  nb_solutions = 1,
  optimality_gap = 0,
  solution_name_prefix = "Solution "
)

Arguments

problem: restopt_problem() Restoration problem object.
precision: integer Precision for calculations. Defaults to 4.
time_limit: integer Maximum permitted run time for optimization (seconds). Defaults to 0.
nb_solutions: integer Number of desired solutions. Defaults to 1.
optimality_gap: numeric Optimality gap (between 0 and 1). For example, an argument of 0.1 means that solutions should be within 10% of optimality. Defaults to 0, such that optimal solutions are returned.
solution_name_prefix: character Prefix for the name of solutions. Defaults to "Solution "

Value

An updated restoration problem (restopt_problem()) object.

Examples

# \donttest{
# load data
habitat_data <- rast(
  system.file("extdata", "habitat_hi_res.tif", package = "restoptr")
)

# create problem
p <- restopt_problem(
    existing_habitat = habitat_data,
    aggregation_factor = 16,
    habitat_threshold = 0.7
  ) %>%
  add_settings(time_limit = 1, precision = 4, nb_solutions = 2)
# print problem
print(p)
#> ----------------------------------------------------------------- 
#>                          Restopt                          
#> ----------------------------------------------------------------- 
#> original habitat:     habitat_hi_res.tif 
#> aggregation factor:   16 
#> habitat threshold:    0.7 
#> existing habitat:     in memory 
#> restorable habitat:   in memory 
#> ----------------------------------------------------------------- 
#> objective:            No optimization objective 
#> ----------------------------------------------------------------- 
#> constraints:         none defined 
#> ----------------------------------------------------------------- 
#> settings: 
#>   - precision = 4
#>   - time_limit = 1
#>   - nb_solutions = 2
#>   - optimality_gap = 0
#>   - solution_name_prefix = Solution  
#> ----------------------------------------------------------------- 
# }