Compile a project prioritization problem() into a general
purpose format for optimization.
compile(x, ...)
# S3 method for ProjectProblem
compile(x, ...)ProjectProblem object.
not used.
OptimizationProblem object.
This function might be useful for those interested in understanding
how their project prioritization problem() is expressed
as a mathematical problem. However, if the problem just needs to
be solved, then the solve() function should be used instead.
# load data
data(sim_projects, sim_features, sim_actions)
# build problem with maximum richness objective, $200 budget, and
# binary decisions
p <- problem(sim_projects, sim_actions, sim_features,
"name", "success", "name", "cost", "name") %>%
add_max_richness_objective(budget = 200) %>%
add_binary_decisions()
# print problem
print(p)
#> Project Prioritization Problem
#> actions F1_action, F2_action, F3_action, ... (6 actions)
#> projects F1_project, F2_project, F3_project, ... (6 projects)
#> features F1, F2, F3, ... (5 features)
#> action costs: min: 0, max: 103.22583
#> project success: min: 0.81379, max: 1
#> objective: Maximum richness objective [budget (200)]
#> targets: none
#> weights: default
#> decisions Binary decision
#> constraints: <none>
#> solver: default
# compile problem
o <- compile(p)
# print compiled problem
print(o)
#> optimization problem
#> objective: linear
#> model sense: max
#> dimensions: 47, 47, 103 (nrow, ncol, ncell)
#> variables: 42 (B), 5 (S)