special_ordered_set_type_1

relationalai.semantics.reasoners.prescriptive

special_ordered_set_type_1(index: Any, variables: Any) -> b.Aggregate

Return an SOS1 constraint (at most one variable is non-zero).

Use this inside Model.require and pass the resulting fragment to Problem.satisfy. Arguments must reference decision variables declared via Problem.solve_for. Commonly used for piecewise-linear formulations.

Parameters

• index

  (Any) - Ordering index used to define the set.

• variables

  (Any) - Decision-variable expression(s) in the SOS1 set.

Returns

• Aggregate - A solver aggregate representing the SOS1 constraint.

Examples

Create nonnegative weights and constrain them with SOS1:

from relationalai.semantics import Float, Integer, Model, std
from relationalai.semantics.reasoners.prescriptive import (
    Problem,
    special_ordered_set_type_1,
)

m = Model("sos1_demo")
Point = m.Concept("Point", identify_by={"i": Integer})
Point.w = m.Property(f"{Point} has {Float:w}")
m.define(Point.new(i=std.common.range(3)))
problem = Problem(m, Float)
problem.solve_for(Point.w, name=["w", Point.i], lower=0)
problem.satisfy(m.require(special_ordered_set_type_1(Point.i, Point.w)))

Referenced By

RelationalAI Documentation
└──  Build With RelationalAI
    └──  Understand how PyRel works > Use advanced reasoning > Prescriptive reasoning
        ├──  Choose a backend
        │   ├──  Use HiGHS
        │   │   └──  Limitations
        │   └──  Use Ipopt
        │       └──  Limitations
        └──  Solve a decision problem
            └──  Add constraints