Sage Reference Manual: Numerical Optimization - Mirrors

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Sage Reference Manual: Numerical Optimization, Release 6.1.1 EXAMPLE: sage: lp = MixedIntegerLinearProgram(solver = ’GLPK’, maximization = False) sage: x, y = lp[0], lp[1] sage: lp.add_constraint(-2*x + y
Sage Reference Manual: Numerical Optimization, Release 6.1.1 sage: P.get_min(x) 0.0 variable_upper_bound(index, value=False) Return or define the upper bound on a variable INPUT: •index (integer) – the variable’s id •value – real value, or None to mean that the variable has not upper bound. When set to False (default), the method returns the current value. EXAMPLE: sage: from sage.numerical.backends.generic_backend import get_solver sage: p = get_solver(solver = "GLPK") sage: p.add_variable() 0 sage: p.col_bounds(0) (0.0, None) sage: p.variable_upper_bound(0, 5) sage: p.col_bounds(0) (0.0, 5.0) TESTS: trac ticket #14581: sage: P = MixedIntegerLinearProgram(solver="GLPK") sage: x = P["x"] sage: P.set_max(x, 0) sage: P.get_max(x) 0.0 write_lp(filename) 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 = "GLPK") sage: p.add_variables(2) 1 sage: p.add_linear_constraint([[0, 1], [1, 2]], None, 3) sage: p.set_objective([2, 5]) sage: p.write_lp(os.path.join(SAGE_TMP, "lp_problem.lp")) Writing problem data to ... 9 lines were written write_mps(filename, modern) Write the problem to a .mps file INPUT: •filename (string) EXAMPLE: 5.2. GLPK Backend 79
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Sage Reference Manual: Numerical Op
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CHAPTER ONE KNAPSACK PROBLEMS This
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CHAPTER TWO MIXED INTEGER LINEAR PR
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Sage Reference Manual: Numerical Optimization - Mirrors

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