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.

No return value.

- $data
`list`

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

- print()
Print basic information of the model solution.

- show()
Call print method.

```
# \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)
#> Rcplex: num variables=10296 num constraints=29984
## Use class methods
s$print()
#> Solution overview
#> name: sol
#> objective value: 863
#> gap: 0%
#> status: Optimal solution (according to gap tolerance: 0)
#> runtime: 2.76 sec
# }
```