Sage Reference Manual: Numerical Optimization - Mirrors
Sage Reference Manual: Numerical Optimization - Mirrors
Sage Reference Manual: Numerical Optimization - Mirrors
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<strong>Sage</strong> <strong>Reference</strong> <strong>Manual</strong>: <strong>Numerical</strong> <strong>Optimization</strong>, Release 6.1.1<br />
([4, 3, 2, 1], [4.0, 3.0, 2.0, 1.0])<br />
sage: p.row_bounds(0)<br />
(2.0, 2.0)<br />
# optional - Nonexistent_LP_solver<br />
row_name(index)<br />
Return the index th row name<br />
INPUT:<br />
•index (integer) – the row’s id<br />
EXAMPLE:<br />
sage: from sage.numerical.backends.generic_backend import get_solver<br />
sage: p = get_solver(solver = "Nonexistent_LP_solver") # optional - Nonexistent_LP_solver<br />
sage: p.add_linear_constraints(1, 2, None, name="Empty constraint 1") # optional - Nonexist<br />
sage: p.row_name(0)<br />
# optional - Nonexistent_LP_solver<br />
’Empty constraint 1’<br />
set_objective(coeff, d=0.0)<br />
Set the objective function.<br />
INPUT:<br />
•coeff – a list of real values, whose ith element is the coefficient of the ith variable in the objective<br />
function.<br />
•d (double) – the constant term in the linear function (set to 0 by default)<br />
EXAMPLE:<br />
sage: from sage.numerical.backends.generic_backend import get_solver<br />
sage: p = get_solver(solver = "Nonexistent_LP_solver") # optional - Nonexistent_LP_solver<br />
sage: p.add_variables(5)<br />
# optional - Nonexistent_LP_solver<br />
5<br />
sage: p.set_objective([1, 1, 2, 1, 3])<br />
# optional - Nonexistent_LP_solver<br />
sage: map(lambda x :p.objective_coefficient(x), range(5)) # optional - Nonexistent_LP_solve<br />
[1.0, 1.0, 2.0, 1.0, 3.0]<br />
Constants in the objective function are respected:<br />
sage: p = MixedIntegerLinearProgram(solver=’Nonexistent_LP_solver’) # optional - Nonexistent<br />
sage: x,y = p[0], p[1]<br />
# optional - Nonexistent_LP_solver<br />
sage: p.add_constraint(2*x + 3*y, max = 6)<br />
# optional - Nonexistent_LP_solver<br />
sage: p.add_constraint(3*x + 2*y, max = 6)<br />
# optional - Nonexistent_LP_solver<br />
sage: p.set_objective(x + y + 7)<br />
# optional - Nonexistent_LP_solver<br />
sage: p.set_integer(x); p.set_integer(y)<br />
# optional - Nonexistent_LP_solver<br />
sage: p.solve()<br />
# optional - Nonexistent_LP_solver<br />
9.0<br />
set_sense(sense)<br />
Set the direction (maximization/minimization).<br />
INPUT:<br />
•sense (integer) :<br />
EXAMPLE:<br />
–+1 => Maximization<br />
–-1 => Minimization<br />
5.1. Generic Backend for LP solvers 57
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