evalBudget | R Documentation |
Return one solution per instance for different values of budgets. This
function assumes that the maximizeBenefits option is being used (note that
the minimizeCosts option does not require setting a maximum budget). Like
prioriactions()
function, it inherits all arguments from inputData()
,
problem()
and solve()
.
evalBudget(values = c(), ...)
values |
|
... |
arguments inherited from |
evalBudget()
creates and solves multiple instances, of the corresponding
multi-actions planning problem, for different values of maximum budgets. Alternatively, this
could be obtained by executing function prioriactions()
or by steps the inputData()
,
problem()
and solve()
functions; using, in each run, different budgets values.
However, the evalBudget()
function has two advantages with
respect to this manual approach: : 1)
it is more efficient to create the models (this is because the model is created
just once and, at each iteration, only the budget values are updated); and 2) the
output is a portfolio object, which allows
obtaining information about the group of solutions (including all get functions).
An object of class portfolio.
# set seed for reproducibility
set.seed(14)
## Create model and solve
port <- evalBudget(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,
values = c(1, 10, 50, 100),
time_limit = 50,
output_file = FALSE,
cores = 2)
getSolutionBenefit(port)
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