Specify for which objectives regret-based FoRDM analysis should be applied. For each objective, define its name, direction, weight, time aggregation method (mean, sum, min or max), and discount rate.
build_objectives_regret(
names,
direction = rep("maximize", length(names)),
weights = rep(1/length(names), length(names)),
time_aggregation = rep("mean", length(names)),
discount_rate = rep(0, length(names))
)A data frame specifying objectives, directions, weights, time aggregation methods, and discount rates for use in FoRDM analysis.
Names of objectives as the column names in the provided data.
Direction of objective function: 'maximize' or 'minimize'.
Relative weights (0-1) for each objective, must sum to 1.
Time aggregation across objectives: 'mean', 'sum', 'min' or 'max'.
Annual discount rates for each objective (e.g., 0.02 means 2% per year), applied during time aggregation.