Sage Reference Manual: Numerical Optimization - Mirrors

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Sage Reference Manual: Numerical Optimization, Release 6.1.1 sage: from sage.numerical.backends.generic_backend import get_solver sage: p = get_solver(solver = "Nonexistent_LP_solver") # optional - Nonexistent_LP_solver sage: p.add_variable() # optional - Nonexistent_LP_solver 1 sage: p.col_bounds(0) # optional - Nonexistent_LP_solver (0.0, None) sage: p.variable_upper_bound(0, 5) # optional - Nonexistent_LP_solver sage: p.col_bounds(0) # optional - Nonexistent_LP_solver (0.0, 5.0) write_lp(name) Write the problem to a .lp file INPUT: •filename (string) EXAMPLE: sage: from sage.numerical.backends.generic_backend import get_solver sage: p = get_solver(solver = "Nonexistent_LP_solver") # optional - Nonexistent_LP_solver sage: p.add_variables(2) # optional - Nonexistent_LP_solver 2 sage: p.add_linear_constraint([(0, 1], (1, 2)], None, 3) # optional - Nonexistent_LP_solver sage: p.set_objective([2, 5]) # optional - Nonexistent_LP_solver sage: p.write_lp(os.path.join(SAGE_TMP, "lp_problem.lp")) # optional - Nonexisten write_mps(name, modern) Write the problem to a .mps file zero() INPUT: •filename (string) EXAMPLE: sage: from sage.numerical.backends.generic_backend import get_solver sage: p = get_solver(solver = "Nonexistent_LP_solver") # optional - Nonexistent_LP_solver sage: p.add_variables(2) # optional - Nonexistent_LP_solver 2 sage: p.add_linear_constraint([(0, 1), (1, 2)], None, 3) # optional - Nonexistent_LP_solver sage: p.set_objective([2, 5]) # optional - Nonexistent_LP_solver sage: p.write_lp(os.path.join(SAGE_TMP, "lp_problem.lp")) # optional - Nonexisten sage.numerical.backends.generic_backend.default_mip_solver(solver=None) Returns/Sets the default MILP Solver used by Sage INPUT: •solver – defines the solver to use: –GLPK (solver="GLPK"). See the GLPK web site. –COIN Branch and Cut (solver="Coin"). See the COIN-OR web site. –CPLEX (solver="CPLEX"). See the CPLEX web site. –Gurobi (solver="Gurobi"). See the Gurobi web site. solver should then be equal to one of "GLPK", "Coin", "CPLEX", or "Gurobi". –If solver=None (default), the current default solver’s name is returned. 60 Chapter 5. LP Solver backends
Sage Reference Manual: Numerical Optimization, Release 6.1.1 OUTPUT: This function returns the current default solver’s name if solver = None (default). Otherwise, it sets the default solver to the one given. If this solver does not exist, or is not available, a ValueError exception is raised. EXAMPLE: sage: former_solver = default_mip_solver() sage: default_mip_solver("GLPK") sage: default_mip_solver() ’Glpk’ sage: default_mip_solver("Yeahhhhhhhhhhh") Traceback (most recent call last): ... ValueError: ’solver’ should be set to ’GLPK’, ’Coin’, ’CPLEX’, ’Gurobi’ or None. sage: default_mip_solver(former_solver) sage.numerical.backends.generic_backend.get_solver(constraint_generation=False, solver=None) Return a solver according to the given preferences INPUT: •solver – 4 solvers should be available through this class: –GLPK (solver="GLPK"). See the GLPK web site. –COIN Branch and Cut (solver="Coin"). See the COIN-OR web site. –CPLEX (solver="CPLEX"). See the CPLEX web site. –Gurobi (solver="Gurobi"). See the Gurobi web site. –PPL (solver="PPL"). See the PPL web site. solver should then be equal to one of "GLPK", "Coin", "CPLEX", "Gurobi", "PPL", or None. If solver=None (default), the default solver is used (see default_mip_solver method. •constraint_generation (boolean) – whether the solver returned is to be used for constraint/variable generation. As the interface with Coin does not support constraint/variable generation, setting constraint_generation to False ensures that the backend to Coin is not returned when solver = None. This is set to False by default. See Also: •default_mip_solver() – Returns/Sets the default MIP solver. EXAMPLE: sage: from sage.numerical.backends.generic_backend import get_solver sage: p = get_solver() 5.2 GLPK Backend GLPK Backend AUTHORS: • Nathann Cohen (2010-10): initial implementation 5.2. GLPK Backend 61
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