97 lines
3.0 KiB
Python
97 lines
3.0 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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"""Minimal example to call the GLOP solver."""
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# [START program]
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# [START import]
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from ortools.init.python import init
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from ortools.linear_solver import pywraplp
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# [END import]
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def main():
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print("Google OR-Tools version:", init.OrToolsVersion.version_string())
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# [START solver]
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# Create the linear solver with the GLOP backend.
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solver = pywraplp.Solver.CreateSolver("GLOP")
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if not solver:
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print("Could not create solver GLOP")
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return
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# [END solver]
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# [START variables]
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# Create the variables x and y.
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x_var = solver.NumVar(0, 1, "x")
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y_var = solver.NumVar(0, 2, "y")
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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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infinity = solver.infinity()
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# Create a linear constraint, x + y <= 2.
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constraint = solver.Constraint(-infinity, 2, "ct")
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constraint.SetCoefficient(x_var, 1)
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constraint.SetCoefficient(y_var, 1)
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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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# Create the objective function, 3 * x + y.
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objective = solver.Objective()
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objective.SetCoefficient(x_var, 3)
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objective.SetCoefficient(y_var, 1)
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objective.SetMaximization()
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# [END objective]
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# [START solve]
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print(f"Solving with {solver.SolverVersion()}")
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result_status = solver.Solve()
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# [END solve]
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# [START print_solution]
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print(f"Status: {result_status}")
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if result_status != pywraplp.Solver.OPTIMAL:
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print("The problem does not have an optimal solution!")
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if result_status == pywraplp.Solver.FEASIBLE:
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print("A potentially suboptimal solution was found")
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else:
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print("The solver could not solve the problem.")
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return
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print("Solution:")
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print("Objective value =", objective.Value())
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print("x =", x_var.solution_value())
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print("y =", y_var.solution_value())
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# [END print_solution]
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# [START advanced]
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print("Advanced 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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if __name__ == "__main__":
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init.CppBridge.init_logging("basic_example.py")
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cpp_flags = init.CppFlags()
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cpp_flags.stderrthreshold = True
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cpp_flags.log_prefix = False
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init.CppBridge.set_flags(cpp_flags)
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main()
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# [END program]
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