a7f49a2585
* rename swig files .i in .swig * update constraint_solver and routing * backport math_opt changes * move dynamic loading to ortools/third_party_solvers
99 lines
3.1 KiB
Python
99 lines
3.1 KiB
Python
#!/usr/bin/env python3
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# Copyright 2010-2025 Google LLC
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Small example to illustrate solving a MIP problem."""
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# [START program]
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# [START import]
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from ortools.linear_solver import pywraplp
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# [END import]
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def IntegerProgrammingExample():
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"""Integer programming sample."""
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# [START solver]
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# Create the mip solver with the SCIP backend.
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solver = pywraplp.Solver.CreateSolver("SCIP")
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if not solver:
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return
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# [END solver]
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# [START variables]
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# x, y, and z are non-negative integer variables.
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x = solver.IntVar(0.0, solver.infinity(), "x")
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y = solver.IntVar(0.0, solver.infinity(), "y")
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z = solver.IntVar(0.0, solver.infinity(), "z")
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print("Number of variables =", solver.NumVariables())
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# [END variables]
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# [START constraints]
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# 2*x + 7*y + 3*z <= 50
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constraint0 = solver.Constraint(-solver.infinity(), 50)
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constraint0.SetCoefficient(x, 2)
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constraint0.SetCoefficient(y, 7)
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constraint0.SetCoefficient(z, 3)
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# 3*x - 5*y + 7*z <= 45
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constraint1 = solver.Constraint(-solver.infinity(), 45)
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constraint1.SetCoefficient(x, 3)
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constraint1.SetCoefficient(y, -5)
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constraint1.SetCoefficient(z, 7)
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# 5*x + 2*y - 6*z <= 37
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constraint2 = solver.Constraint(-solver.infinity(), 37)
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constraint2.SetCoefficient(x, 5)
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constraint2.SetCoefficient(y, 2)
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constraint2.SetCoefficient(z, -6)
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print("Number of constraints =", solver.NumConstraints())
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# [END constraints]
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# [START objective]
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# Maximize 2*x + 2*y + 3*z
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objective = solver.Objective()
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objective.SetCoefficient(x, 2)
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objective.SetCoefficient(y, 2)
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objective.SetCoefficient(z, 3)
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objective.SetMaximization()
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# [END objective]
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# Solve the problem.
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# [START solve]
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print(f"Solving with {solver.SolverVersion()}")
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status = solver.Solve()
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# [END solve]
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# Print the solution.
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# [START print_solution]
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if status == pywraplp.Solver.OPTIMAL:
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print("Solution:")
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print(f"Objective value = {solver.Objective().Value()}")
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# Print the value of each variable in the solution.
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for variable in [x, y, z]:
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print(f"{variable.name()} = {variable.solution_value()}")
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else:
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print("The problem does not have an optimal solution.")
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# [END print_solution]
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# [START advanced]
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print("\nAdvanced usage:")
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print(f"Problem solved in {solver.wall_time():d} milliseconds")
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print(f"Problem solved in {solver.iterations():d} iterations")
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# [END advanced]
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IntegerProgrammingExample()
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# [END program]
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