Update CHANGELOG

CHANGELOG.md

@@ -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