ortools.math_opt.python.model Namespace Reference

Detailed Description

A solver independent library for modeling optimization problems.

Example use to model the optimization problem:
   max 2.0 * x + y
   s.t. x + y <= 1.5
            x in {0.0, 1.0}
            y in [0.0, 2.5]

  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')
  # We can directly use linear combinations of variables ...
  model.add_linear_constraint(x + y <= 1.5, name='c')
  # ... or build them incrementally.
  objective_expression = 0
  objective_expression += 2 * x
  objective_expression += y
  model.maximize(objective_expression)

  # May raise a RuntimeError on invalid input or internal solver errors.
  result = mathopt.solve(model, mathopt.SolverType.GSCIP)

  if result.termination.reason not in (mathopt.TerminationReason.OPTIMAL,
                                       mathopt.TerminationReason.FEASIBLE):
    raise RuntimeError(f'model failed to solve: {result.termination}')

  print(f'Objective value: {result.objective_value()}')
  print(f'Value for variable x: {result.variable_values()[x]}')

Classes
class	Model
class	UpdateTracker