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Update CHANGELOG
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CHANGELOG.md
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CHANGELOG.md
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All notable changes to this project will be documented in this file.
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All notable changes to this project will be documented in this file.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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and this project adheres to
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[Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [0.4.1] - 2024-12-10
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## Changed
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- H5File: Use float64 precision instead of float32
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- LearningSolver: optimize now returns (model, stats) instead of just stats
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- Update dependency: Gurobi 11
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## [0.4.0] - 2024-02-06
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## [0.4.0] - 2024-02-06
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### Changed
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### Changed
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- LearningSolver.solve no longer generates HDF5 files; use a collector instead.
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- LearningSolver.solve no longer generates HDF5 files; use a collector instead.
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- Add `_gurobipy` suffix to all `build_model` functions; implement some `_pyomo` and `_jump` functions.
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- Add `_gurobipy` suffix to all `build_model` functions; implement some `_pyomo`
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and `_jump` functions.
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## [0.3.0] - 2023-06-08
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## [0.3.0] - 2023-06-08
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This is a complete rewrite of the original prototype package, with an entirely new API, focused on performance, scalability and flexibility.
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This is a complete rewrite of the original prototype package, with an entirely
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new API, focused on performance, scalability and flexibility.
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### Added
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### Added
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- Add support for Python/Gurobipy and Julia/JuMP, in addition to the existing Python/Pyomo interface.
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- Add support for Python/Gurobipy and Julia/JuMP, in addition to the existing
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- Add six new random instance generators (bin packing, capacitated p-median, set cover, set packing, unit commitment, vertex cover), in addition to the three existing generators (multiknapsack, stable set, tsp).
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Python/Pyomo interface.
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- Collect some additional raw training data (e.g. basis status, reduced costs, etc)
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- Add six new random instance generators (bin packing, capacitated p-median, set
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- Add new primal solution ML strategies (memorizing, independent vars and joint vars)
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cover, set packing, unit commitment, vertex cover), in addition to the three
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- Add new primal solution actions (set warm start, fix variables, enforce proximity)
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existing generators (multiknapsack, stable set, tsp).
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- Collect some additional raw training data (e.g. basis status, reduced costs,
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etc)
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- Add new primal solution ML strategies (memorizing, independent vars and joint
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vars)
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- Add new primal solution actions (set warm start, fix variables, enforce
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proximity)
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- Add runnable tutorials and user guides to the documentation.
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- Add runnable tutorials and user guides to the documentation.
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### Changed
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### Changed
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- To support large-scale problems and datasets, switch from an in-memory architecture to a file-based architecture, using HDF5 files.
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- To support large-scale problems and datasets, switch from an in-memory
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- To accelerate development cycle, split training data collection from feature extraction.
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architecture to a file-based architecture, using HDF5 files.
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- To accelerate development cycle, split training data collection from feature
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extraction.
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### Removed
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### Removed
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- Temporarily remove ML strategies for lazy constraints
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- Temporarily remove ML strategies for lazy constraints
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- Remove benchmarks from documentation. These will be published in a separate paper.
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- Remove benchmarks from documentation. These will be published in a separate
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paper.
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## [0.1.0] - 2020-11-23
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## [0.1.0] - 2020-11-23
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