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()