Sage Reference Manual: Numerical Optimization - Mirrors

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Sage Reference Manual: Numerical Optimization, Release 6.1.1 sage: p = MixedIntegerLinearProgram() sage: v = p.new_variable() sage: p.set_objective(v[1]) sage: p.get_min(v[1]) 0.0 sage: p.set_min(v[1],6) sage: p.get_min(v[1]) 6.0 sage: p.set_min(v[1], None) sage: p.get_min(v[1]) set_objective(obj) Sets the objective of the MixedIntegerLinearProgram. INPUT: •obj – A linear function to be optimized. ( can also be set to None or 0 when just looking for a feasible solution ) EXAMPLE: Let’s solve the following linear program: Maximize: x + 5 * y Constraints: x + 0.2 y
Sage Reference Manual: Numerical Optimization, Release 6.1.1 •ee – An instance of MIPVariable or one of its elements. EXAMPLE: sage: p = MixedIntegerLinearProgram() sage: x = p.new_variable() With the following instruction, all the variables from x will be real (they are by default, though): sage: p.set_real(x) sage: p.set_objective(x[0] + x[1]) sage: p.add_constraint(-3*x[0] + 2*x[1], max=2) It is still possible, though, to set one of these variables as binary while keeping the others as they are:: sage: p.set_binary(x[3]) show() Displays the MixedIntegerLinearProgram in a human-readable way. EXAMPLES: When constraints and variables have names sage: p = MixedIntegerLinearProgram(solver = "GLPK") sage: x = p.new_variable(name="Hey") sage: p.set_objective(x[1] + x[2]) sage: p.add_constraint(-3*x[1] + 2*x[2], max=2, name="Constraint_1") sage: p.show() Maximization: Hey[1] + Hey[2] Constraints: Constraint_1: -3.0 Hey[1] + 2.0 Hey[2]
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Page 5 and 6: CHAPTER ONE KNAPSACK PROBLEMS This
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CHAPTER SIX INDICES AND TABLES •
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BIBLIOGRAPHY [HPS08] J. Hoffstein,
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PYTHON MODULE INDEX n sage.numerica
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INDEX A add_col() (sage.numerical.b
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