Compile a conservation planning problem()
into an
(potentially mixed) integer linear programming problem.
compile(x, ...) # S3 method for ConservationProblem compile(x, compressed_formulation = NA, ...)
x 


...  not used. 
compressed_formulation 

OptimizationProblem
object.
This function might be useful for those interested in understanding
how their conservation planning problem()
is expressed
as a mathematical problem. However, if the problem just needs to
be solved, then the solve()
function should just be used.
Please note that in nearly all cases, the default argument to
formulation
should be used. The only situation where manually
setting the argument to formulation
is desirable is during testing.
Manually setting the argument to formulation
will at best
have no effect on the problem. At worst, it may result in
an error, a misspecified problem, or unnecessarily long
solve times.
# build minimal conservation problem p < problem(sim_pu_raster, sim_features) %>% add_min_set_objective() %>% add_relative_targets(0.1) # compile the conservation problem into an optimization problem o < compile(p) # print the optimization problem print(o)#>#> #> #>