MIPLearn/CHANGELOG.md

MIPLearn: Changelog

[Unreleased]

Added

• Added two new machine learning components:
  • Added StaticLazyConstraintComponent, which allows the user to mark some constraints in the formulation as lazy, instead of constructing them in a callback. ML predicts which static lazy constraints should be kept in the formulation, and which should be removed.
  • Added UserCutComponents, which predicts which user cuts should be generated and added to the formulation as constraints ahead-of-time, before solving the MIP.
• Added support to additional MILP solvers:
  • Added support for CPLEX and XPRESS, through the Pyomo modeling language, in addition to (existing) Gurobi. The solver classes are named CplexPyomoSolver, XpressPyomoSolver and GurobiPyomoSolver.
  • Added support for Gurobi without any modeling language. The solver class is named GurobiSolver. In this case, instance.to_model should return gp.Model object.
  • Added support to direct MPS files, produced externally, through the GurobiSolver class mentioned above.
• Added dynamic thresholds:
  • In previous versions of the package, it was necessary to manually adjust component aggressiveness to reach a desired precision/recall. This can now be done automatically with MinProbabilityThreshold, MinPrecisionThreshold and MinRecallThreshold.
• Reduced memory requirements:
  • Previous versions of the package required all training instances to be kept in memory at all times, which was prohibitive for large-scale problems. It is now possible to store instances in file until they are needed, using PickledGzInstance.
• Refactoring:
  • Added static types to all classes (with mypy).

Changed

• Variables are now referenced by their names, instead of tuples (var_name, index). This change was required to improve the compatibility with modeling languages other than Pyomo, which do not follow this convention. The functions get_variable_category and get_variable_features now have the following signature:

   def get_variable_features(self, var_name: str) -> List[float]:
      pass
  
   def get_variable_category(self, var_name: str) -> Optional[Hashable]:
      pass  
  

• Internal solvers must now be specified as objects, instead of strings. For example,

  solver = LearningSolver(
      solver=GurobiPyomoSolver(
          params={
              "TimeLimit": 300,
              "Threads": 4,
          }      
      )
  )
  

• LazyConstraintComponent has been renamed to DynamicLazyConstraintsComponent.

Removed

• Temporarily removed the experimental BranchPriorityComponent. This component will be re-added in the Julia version of the package.
• Removed solver.add method, previously used to add components to an existing solver. Use the constructor LearningSolver(components=[...]) instead.

[0.1.0] - 2020-11-23

• Initial public release