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# MIPLearn: Changelog
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## [Unreleased]
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### Added
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- **Added two new machine learning components:**
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- 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.
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- Added `UserCutComponents`, which predicts which user cuts should be generated and added to the formulation as constraints ahead-of-time, before solving the MIP.
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- **Added support to additional MILP solvers:**
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- 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`.
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- 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.
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- Added support to direct MPS files, produced externally, through the `GurobiSolver` class mentioned above.
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- **Added dynamic thresholds:**
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- 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`.
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- **Reduced memory requirements:**
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- 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`.
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- **Refactoring:**
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- Added static types to all classes (with mypy).
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### Changed
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- **Variables are now referenced by their names,** instead of tuples `(var_name, index)`. This change was required to improve the compatibility with other modeling languages, which do not follow this convention. The functions `get_variable_category` and `get_variable_features` now have the following signature:
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````python
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def get_variable_features(self, var_name: str) -> List[float]:
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pass
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def get_variable_category(self, var_name: str) -> Optional[Hashable]:
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pass
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````
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- **Features are now represented as a list of floating point numbers,** as indicated in the snipped above. This change was required for performance reasons. Returning numpy arrays is no longer supported.
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- **Internal solvers must now be specified as objects, instead of strings.** For example,
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```python
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solver = LearningSolver(
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solver=GurobiPyomoSolver(
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params={
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"TimeLimit": 300,
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"Threads": 4,
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}
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)
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)
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```
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- `LazyConstraintComponent` has been renamed to `DynamicLazyConstraintsComponent`.
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### Removed
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- Temporarily remove the experimental `BranchPriorityComponent`. This component will be re-added in the Julia version of the package.
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- Removed `solver.add` methods, previously used to add components to an existing solver. Use `LearningSolver(components=[...])` instead.
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## [0.1.0] - 2020-11-23
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- Initial public release
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