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Update CHANGELOG

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Alinson S. Xavier
2024-12-10 11:04:40 -06:00
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CHANGELOG.md
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@@ -3,7 +3,16 @@
All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
and this project adheres to
[Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [0.4.1] - 2024-12-10
## Changed
- H5File: Use float64 precision instead of float32
- LearningSolver: optimize now returns (model, stats) instead of just stats
- Update dependency: Gurobi 11
## [0.4.0] - 2024-02-06
@@ -15,31 +24,41 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
### Changed
- LearningSolver.solve no longer generates HDF5 files; use a collector instead.
- Add `_gurobipy` suffix to all `build_model` functions; implement some `_pyomo` and `_jump` functions.
- Add `_gurobipy` suffix to all `build_model` functions; implement some `_pyomo`
and `_jump` functions.
## [0.3.0] - 2023-06-08
This is a complete rewrite of the original prototype package, with an entirely new API, focused on performance, scalability and flexibility.
This is a complete rewrite of the original prototype package, with an entirely
new API, focused on performance, scalability and flexibility.
### Added
- Add support for Python/Gurobipy and Julia/JuMP, in addition to the existing Python/Pyomo interface.
- 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).
- Collect some additional raw training data (e.g. basis status, reduced costs, etc)
- Add new primal solution ML strategies (memorizing, independent vars and joint vars)
- Add new primal solution actions (set warm start, fix variables, enforce proximity)
- Add support for Python/Gurobipy and Julia/JuMP, in addition to the existing
Python/Pyomo interface.
- 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).
- Collect some additional raw training data (e.g. basis status, reduced costs,
etc)
- Add new primal solution ML strategies (memorizing, independent vars and joint
vars)
- Add new primal solution actions (set warm start, fix variables, enforce
proximity)
- Add runnable tutorials and user guides to the documentation.
### Changed
- To support large-scale problems and datasets, switch from an in-memory architecture to a file-based architecture, using HDF5 files.
- To accelerate development cycle, split training data collection from feature extraction.
- To support large-scale problems and datasets, switch from an in-memory
architecture to a file-based architecture, using HDF5 files.
- To accelerate development cycle, split training data collection from feature
extraction.
### Removed
- Temporarily remove ML strategies for lazy constraints
- Remove benchmarks from documentation. These will be published in a separate paper.
- Remove benchmarks from documentation. These will be published in a separate
paper.
## [0.1.0] - 2020-11-23