Skip to contents

Get raw decision vector from a solution set

Source: R/get_solution.R
get_solution_vector.Rd

Return the raw decision-variable vector for a selected run in a solutionset-class object returned by solve.

The vector is returned in the internal model-variable order used by the optimization backend.

Usage

get_solution_vector(x, run = NULL, solution_id = NULL)

Arguments

x

A solutionset-class object returned by solve.

run

Optional positive integer giving the run id to extract. If NULL, the first stored solution is used unless solution_id is supplied.

solution_id

Optional character string giving the solution id to extract. If supplied, run must be NULL.

Value

A numeric vector with one value per internal model variable.

Details

This function extracts the raw decision vector for one run. The returned vector is in the internal variable order of the optimization model. Depending on the problem formulation, it may include:

  • planning-unit selection variables;

  • action-allocation variables;

  • auxiliary variables introduced for targets, budgets, fragmentation, or other constraints/objectives;

  • and potentially additional blocks created internally by the model builder.

Therefore, this vector is primarily intended for advanced users, debugging, diagnostics, or internal verification. It is not a user-facing allocation table.

To inspect selected planning units or selected actions in a more interpretable form, use get_pu or get_actions instead.

See also

get_pu, get_actions, get_features, get_targets

Examples

pu <- data.frame(
  id = 1:4,
  cost = c(1, 2, 3, 4)
)

features <- data.frame(
  id = 1:2,
  name = c("sp1", "sp2")
)

dist_features <- data.frame(
  pu = c(1, 1, 2, 3, 4),
  feature = c(1, 2, 2, 1, 2),
  amount = c(5, 2, 3, 4, 1)
)

problem <- create_problem(
  pu = pu,
  features = features,
  dist_features = dist_features,
  cost = "cost"
) |>
  add_constraint_targets_relative(0.05) |>
  add_objective_min_cost(alias = "cost")

if (requireNamespace("rcbc", quietly = TRUE)) {
  problem <- set_solver_cbc(
    problem,
    verbose = FALSE
  )

  solutions <- solve(problem)

  # Extract the first stored raw solution vector
  vector <- get_solution_vector(solutions)
  vector
  length(vector)

  # Extract a vector using its solution_id
  runs <- get_runs(solutions)
  solution_ids <- runs$solution_id[
    !is.na(runs$solution_id)
  ]

  if (length(solution_ids) > 0L) {
    get_solution_vector(
      solutions,
      solution_id = solution_ids[1]
    )
  }
}
#>  [1] 1 0 0 0 1 0 0 0 0 0 0 0 0