add_manual_locked_constraints: Add manually specified locked constraints

In oppr: Optimal Project Prioritization

Add manually specified locked constraints

Description

Add constraints to a project prioritization problem() to ensure that solutions fund (or do not fund) specific actions. This function offers more fine-grained control than the add_locked_in_constraints() and add_locked_out_constraints() functions.

Usage

add_manual_locked_constraints(x, locked)

## S4 method for signature 'ProjectProblem,data.frame'
add_manual_locked_constraints(x, locked)

## S4 method for signature 'ProjectProblem,tbl_df'
add_manual_locked_constraints(x, locked)

Arguments

x	ProjectProblem object.
locked	data.frame or tibble::tibble() object. See the Details section for more information.

Details

The argument to locked must contain the following fields (columns):

"action"

character action name.

"status"

numeric values indicating if actions should be funded (with a value of 1) or not (with a value of zero).

Value

ProjectProblem object with the constraints added to it.

See Also

constraints.

Examples

# load data
data(sim_projects, sim_features, sim_actions)


# create data frame with locked statuses
status <- data.frame(action = sim_actions$name[1:2],
                     status = c(0, 1))

# print locked statuses
print(status)

# build problem with minimum set objective and targets that require each
# feature to have a 30% chance of persisting into the future
p <- problem(sim_projects, sim_actions, sim_features,
             "name", "success", "name", "cost", "name") %>%
      add_max_richness_objective(budget = 500) %>%
      add_manual_locked_constraints(status) %>%
      add_binary_decisions()

# print problem
print(p)

## Not run: 
# solve problem
s <- solve(p)

# print solution
print(s)

## End(Not run)

oppr documentation built on Sept. 8, 2022, 5:07 p.m.