Skip to content

Qiskit Optimization 0.4.0

Compare
Choose a tag to compare
@manoelmarques manoelmarques released this 29 Jun 17:14
· 132 commits to main since this release
545924c

Changelog

New Features

  • Adds a method prettyprint() to QuadraticProgram to generate a pretty-printed string of the object.

  • Adds informative text formats to str and repr functions of the following objects. The formats are IDE friendly, i.e., the text is one line.

     LinearConstraint
     LinearExpression
     QuadraticConstraint
     QuadraticExpression
     QuadraticObjective
     Variable
    
  • Adds a method prettyprint() to OptimizationResult to display the result in a multi-line text format.

Upgrade Notes

  • If users set an empty variable name "" with binary_var(), integer_var(), and continuous_var(), they set the default variable name (e.g., x0) while they used to set the empty name as variable name.

  • Added support for running with Python 3.10. At the the time of the release, Cplex didn’t have a python 3.10 version and Docplex failed inside docplex.mp.model.Model.binary_var_list().

  • Updates the text format of str and repr of the following objects so that the output is one line.

    QuadraticProgram
    OptimizationResult

  • The previously deprecated BaseBackend class has been removed. It was originally deprecated in the Qiskit Terra 0.18.0 release.

  • Enable installation of CPLEX for Python 3.10.

  • Support for running with Python 3.6 has been removed. To run Optimization you need a minimum Python version of 3.7.

Bug Fixes

  • Fixed an issue that from_ising() raises an error when Pauli I is given.
  • Fixed an issue that to_ising() returns a wrong operator when there is no variable in an input problem.

Other Notes

  • Shows a warning message if non-printable strings are set to QuadraticProgram as problem name, variable name, or constraint name.
  • Updated the documentation of SUCCESS of OptimizationResultStatus. SUCCESS means the obtained solution is feasible, but not always optimal because some algorithms do not guarantee the optimality.
  • Reword the documentation of all methods and the multi-line text format of OptimizationResult as follows because some algorithms do not guarantee the optimality.
    “optimal function value” → “objective function value”
    “optimal value” → “variable values”