InequalityToEquality
InequalityToEquality
Convert inequality constraints into equality constraints by introducing slack variables.
Examples
>>> from qiskit.optimization.problems import QuadraticProgram
>>> from qiskit.optimization.converters import InequalityToEquality
>>> problem = QuadraticProgram()
>>> # define a problem
>>> conv = InequalityToEquality()
>>> problem2 = conv.encode(problem)Methods
decode
InequalityToEquality.decode(result)
Convert a result of a converted problem into that of the original problem.
Parameters
result (OptimizationResult) – The result of the converted problem.
Return type
OptimizationResult
Returns
The result of the original problem.
encode
InequalityToEquality.encode(op, name=None, mode='auto')
Convert a problem with inequality constraints into one with only equality constraints.
Parameters
-
op (
QuadraticProgram) – The problem to be solved, that may contain inequality constraints. -
name (
Optional[str]) – The name of the converted problem. -
mode (
str) –To chose the type of slack variables. There are 3 options for mode.
-
’integer’: All slack variables will be integer variables.
-
’continuous’: All slack variables will be continuous variables
-
’auto’: Try to use integer variables but if it’s not possible,
use continuous variables
-
Return type
Returns
The converted problem, that contain only equality constraints.
Raises
- QiskitOptimizationError – If a variable type is not supported.
- QiskitOptimizationError – If an unsupported mode is selected.
- QiskitOptimizationError – If an unsupported sense is specified.