L'exemple suivant montre comment créer un problème d'optimisation mathématique à l'aide de MathOpt et comment le résoudre à distance à l'aide de l'API OR. Pour obtenir une clé API, commencez par suivre le guide de configuration. MathOpt est disponible dans OR-Tools depuis la version 9.9. Pour en savoir plus, consultez le guide d'installation.
# solve_math_opt_model_via_http.py
"""Example of solving a MathOpt model through the OR API.
The model is built using the Python API, and the corresponding proto is
serialized to JSON to make the HTTP request.
"""
from collections.abc import Sequence
from absl import app
from absl import flags
from ortools.math_opt.python import mathopt
from ortools.math_opt.python.ipc import remote_http_solve
_API_KEY = flags.DEFINE_string("api_key", None, "API key for the OR API")
def request_example() -> None:
"""Endpoint for the Operations Research API.
https://optimization.googleapis.com/v1/mathopt:solveMathOptModel
"""
# Set up the API key and endpoint.
api_key = _API_KEY.value
if not api_key:
print(
"API key is required. See"
" https://developers.google.com/optimization/service/setup for"
" instructions."
)
return
# Build a MathOpt model
model = mathopt.Model(name="my_model")
x = model.add_binary_variable(name="x")
y = model.add_variable(lb=0.0, ub=2.5, name="y")
model.add_linear_constraint(x + y <= 1.5, name="c")
model.maximize(2 * x + y)
try:
result, logs = remote_http_solve.remote_http_solve(
model, mathopt.SolverType.GSCIP, api_key=api_key
)
print(result)
print(logs)
except remote_http_solve.OptimizationServiceError as err:
print(err)
def main(argv: Sequence[str]) -> None:
del argv # Unused.
request_example()
if __name__ == "__main__":
app.run(main)