Create and solve a multi-actions planning problem. It can be used
instead of following the sequence of the inputData()
, problem()
and solve()
functions.
prioriactions(...)
arguments inherited from inputData()
, problem()
and solve()
functions.
An object of class solution.
# \donttest{
## This example uses input files included into package.
## 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
s <- prioriactions(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,
model_type = "minimizeCosts",
time_limit = 50,
output_file = FALSE,
cores = 2)
#> Warning: The blm argument was set to 0, so the boundary data has no effect
#> Warning: Some blm_actions argument were set to 0, so the boundary data has no effect for these cases
#> Rcplex: num variables=396 num constraints=284
print(s)
#> Solution overview
#> name: sol
#> objective value: 738
#> gap: 0%
#> status: Optimal solution (according to gap tolerance: 0)
#> runtime: 0.013 sec
# }