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45 lines
2.9 KiB
45 lines
2.9 KiB
# MIPLearn: Changelog
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## [0.2.0] - [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 modeling languages other than Pyomo, which do not follow this convention. For performance reasons, the functions `get_variable_features` and `get_variable_categories` should now return a dictionary containing categories and features for all relevant variables. Previously, MIPLearn had to perform two function calls per variable, which was too slow for very large models.
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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 removed the experimental `BranchPriorityComponent`. This component will be re-added in the Julia version of the package.
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- Removed `solver.add` method, previously used to add components to an existing solver. Use the constructor `LearningSolver(components=[...])` instead.
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## [0.1.0] - 2020-11-23
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- Initial public release
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