multi_compile: Compile a multi-objective optimization problem

In prioritizr: Systematic Conservation Prioritization in R

Compile a multi-objective optimization problem

Description

Compile multiple OptimizationProblem objects for multi-objective optimization.

Usage

multi_compile(x, ...)

## S3 method for class 'MultiConservationProblem'
multi_compile(x, ...)

## S3 method for class 'list'
multi_compile(x, ...)

Arguments

x	multi_problem() or list of OptimizationProblem objects.
...	arguments passed to compile().

Value

A list containing a (⁠$obj⁠) numeric matrix with the coefficients for each of the objectives (i.e., rows correspond to different objectives and columns correspond to different decision variables), (⁠$modelsense⁠) character vector indicating if each objective should be maximized or minimized (i.e., each element corresponds to a different objective), and a (⁠$opt⁠) OptimizationProblem object with all of the constraints present in x (note that the objective coefficients in the returned object are all zero).

See Also

See compile() to create an OptimizationProblem object.

Examples

# import data
sim_pu_raster <- get_sim_pu_raster()
sim_features <- get_sim_features()

# define a total conservation budget (30% of total cost)
budget <- terra::global(sim_pu_raster, "sum", na.rm = TRUE)[[1]] * 0.3

# create multi-objective conservation planning problem
mp <-
  multi_problem(
    keystone_obj =
      problem(sim_pu_raster, sim_features[[1:3]]) %>%
      add_min_shortfall_objective(budget) %>%
      add_relative_targets(0.4) %>%
      add_binary_decisions(),
    iconic_obj =
      problem(sim_pu_raster, sim_features[[4:5]]) %>%
      add_min_shortfall_objective(budget) %>%
      add_relative_targets(0.45) %>%
      add_binary_decisions()
  )

# compile into multi-objective optimization problem
mo <- multi_compile(mp)

# print multi-objective optimization problem
print(mo)

prioritizr documentation built on Sept. 24, 2026, 5:07 p.m.