Specify that the best solver currently available should be used to solve a conservation planning problem.
Arguments
- x
problem()
object.- ...
arguments passed to the solver.
Value
An updated problem()
object with the solver added to it.
Details
Ranked from best to worst, the available solvers that can be used are:
add_gurobi_solver()
, add_cplex_solver()
, add_cbc_solver()
,
add_highs_solver()
, add_lpsymphony_solver()
, and finally
add_rsymphony_solver()
.
For information on the performance of different solvers,
please see Schuster et al. (2020).
References
Schuster R, Hanson JO, Strimas-Mackey M, and Bennett JR (2020). Exact integer linear programming solvers outperform simulated annealing for solving conservation planning problems. PeerJ, 8: e9258.
See also
See solvers for an overview of all functions for adding a solver.
Other solvers:
add_cbc_solver()
,
add_cplex_solver()
,
add_gurobi_solver()
,
add_highs_solver()
,
add_lsymphony_solver
,
add_rsymphony_solver()