This class is used to represent the solution of the MIP (Mixed-Integer Programming) model. This includes several methods to obtain information about both the optimization process and the solution associated with the planning units and actions. It is created using the solve() function.

Value

No return value.

Fields

$data

list. Object containing data on the results of the optimization process.

Methods

print()

Print basic information of the model solution.

show()

Call print method.

Examples

# \donttest{
# set seed for reproducibility
set.seed(14)

## Load data
data(sim_pu_data, sim_features_data, sim_dist_features_data,
sim_threats_data, sim_dist_threats_data, sim_sensitivity_data,
sim_boundary_data)

## Create data instance
problem_data <- inputData(
  pu = sim_pu_data, features = sim_features_data, dist_features = sim_dist_features_data,
  threats = sim_threats_data, dist_threats = sim_dist_threats_data,
  sensitivity = sim_sensitivity_data, boundary = sim_boundary_data
)

## Create optimization model
problem_model <- problem(x = problem_data, blm = 1)
#> Warning: Some blm_actions argument were set to 0, so the boundary data has no effect for these cases

## Solve the optimization model
s <- solve(a = problem_model, time_limit = 5, output_file = FALSE, cores = 2)

## Use class methods

s$print()
#> Solution overview
#>   name: sol
#>   objective value: 863
#>   gap:  0%
#>   status:  Optimal solution (according to gap tolerance: 0)
#>   runtime: 0.001 sec
# }