63 lines
2.1 KiB
Python
63 lines
2.1 KiB
Python
#!/usr/bin/env python3
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# Copyright 2010-2024 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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"""Simple linear programming example."""
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from typing import Sequence
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from absl import app
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from ortools.math_opt.python import mathopt
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# Model and solve the problem:
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# max 10 * x0 + 6 * x1 + 4 * x2
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# s.t. 10 * x0 + 4 * x1 + 5 * x2 <= 600
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# 2 * x0 + 2 * x1 + 6 * x2 <= 300
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# x0 + x1 + x2 <= 100
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# x0 in [0, infinity)
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# x1 in [0, infinity)
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# x2 in [0, infinity)
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#
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def main(argv: Sequence[str]) -> None:
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del argv # Unused.
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model = mathopt.Model(name="Linear programming example")
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# Variables
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x = [model.add_variable(lb=0.0, name=f"x{j}") for j in range(3)]
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# Constraints
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model.add_linear_constraint(10 * x[0] + 4 * x[1] + 5 * x[2] <= 600, name="c1")
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model.add_linear_constraint(2 * x[0] + 2 * x[1] + 6 * x[2] <= 300, name="c2")
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model.add_linear_constraint(sum(x) <= 100, name="c3")
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# Objective
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model.maximize(10 * x[0] + 6 * x[1] + 4 * x[2])
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# May raise a RuntimeError on invalid input or internal solver errors.
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result = mathopt.solve(model, mathopt.SolverType.GLOP)
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if result.termination.reason != mathopt.TerminationReason.OPTIMAL:
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raise RuntimeError(f"model failed to solve to optimality: {result.termination}")
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print(f"Problem solved in {result.solve_time()}")
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print(f"Objective value: {result.objective_value()}")
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variable_values = [result.variable_values()[v] for v in x]
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print(f"Variable values: {variable_values}")
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if __name__ == "__main__":
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app.run(main)
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