evalBlm {prioriactions}

Evaluate multiple blm values

Description

Return one solution per instance for different values of blm. Like prioriactions() function, it inherits all arguments from inputData(), problem() and solve().

Usage

evalBlm(values = c(), ...)

Arguments

values

numeric. Values of blm to verify. More than one value is needed.

...

arguments inherited from inputData(), problem() and solve() functions.

Details

evalblm() creates and solves multiple instances, of the corresponding multi-actions planning problem, for different values of blm. Alternatively, this could be obtained by executing function prioriactions() or by steps the inputData(), problem() and solve() functions; using, in each run, different blm values. However, the evalblm() 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 blm values are updated); and 2) the output is a portfolio object, which allows obtaining information about the group of solutions (including all get functions).

Value

An object of class portfolio.

Examples

# set seed for reproducibility
set.seed(14)

## Create model and solve
port <- evalBlm(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(0.0, 0.01, 0.02, 0.03),
                model_type = "minimizeCosts",
                time_limit = 50,
                output_file = FALSE,
                cores = 2)

getConnectivityPenalty(port)