sasoptpy.Constraint

class Constraint(**kwargs)

Bases: sasoptpy.core.expression.Expression

Creates a linear or quadratic constraint for optimization models

Constraints should be created by adding logical relations to Expression objects.

Parameters

expExpression

A logical expression that forms the constraint

directionstring, optional

Direction of the logical expression

Possible values are

• E for equality (=) constraints

• L for less than or euqal to (<=) constraints

• G for greater than or equal to (>=) constraints

namestring, optional

Name of the constraint object

crangefloat, optional

Range for ranged constraints

See also

sasoptpy.Model.add_constraint()

Notes

• A constraint can be generated in two different ways:

  • Using the sasoptpy.Model.add_constraint() method

    >>> m = so.Model(name='m')
    >>> c1 = m.add_constraint(3 * x - 5 * y <= 10, name='c1')
    >>> print(repr(c1))
    sasoptpy.Constraint( -  5.0 * y  +  3.0 * x  <=  10, name='c1')
    

  • Using the constructor

    >>> c1 = sasoptpy.Constraint(3 * x - 5 * y <= 10, name='c1')
    >>> print(repr(c1))
    sasoptpy.Constraint( -  5.0 * y  +  3.0 * x  <=  10, name='c1')
    

• The same constraint can be included into other models using the Model.include() method.

Examples

>>> x = so.Variable(name='x')
>>> y = so.Variable(name='y')
>>> c1 = so.Constraint( 3 * x - 5 * y <= 10, name='c1')
>>> print(repr(c1))
sasoptpy.Constraint( -  5.0 * y  +  3.0 * x  <=  10, name='c1')

>>> c2 = so.Constraint( - x + 2 * y - 5, direction='L', name='c2')
sasoptpy.Constraint( -  x  +  2.0 * y  <=  5, name='c2')