def _solve_optimization(self, solver: pywraplp.Solver) -> None:
# The MIP solver is usually fast (milliseconds). If we hit a weird problem,
# accept a suboptimal solution after 10 seconds.
solver.SetTimeLimit(10000)
status = solver.Solve()
if status == pywraplp.Solver.INFEASIBLE:
raise Exception("Infeasible problem")
elif status == pywraplp.Solver.NOT_SOLVED:
raise Exception("Problem unsolved")
def _solve_optimization(self, solver: pywraplp.Solver) -> bool:
# The MIP solver is usually fast (milliseconds). If we hit a weird problem,
# accept a suboptimal solution after 10 seconds.
solver.SetTimeLimit(10000)
status = solver.Solve()
if status == pywraplp.Solver.INFEASIBLE:
logger.warning("Optimization problem is infeasible")
return False
elif status == pywraplp.Solver.NOT_SOLVED:
logger.warning("Optimization problem could not be solved in time")
return False
return True