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Specify that the best solver currently available should be used to solve a conservation planning problem.


add_default_solver(x, ...)



problem() object.


arguments passed to the solver.


An updated problem() object with the solver added to it.


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).


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()