v4.0.0

🚀 What's New
Full Support for Multi-Objective Optimization
Version 4.0.0 marks a major milestone for Opytimizer, introducing a robust architecture for multi-objective optimization problems. Key highlights include:
Modular Multi-Objective Architecture
New modules under opytimizer/optimizers/multi_objective/ implementing classic algorithms such as NSGA-II, SPEA2, MOEA/D, MOEA/D-DE, and more.
Support for multi-objective functions via opytimizer/functions/multi_objective/ and classes like WeightedFunction.
Search spaces adapted for multi-objective problems, with automatic Pareto front updates.
Pareto Front Visualization
New visualization tools in opytimizer/visualization/multi_objective.py to plot Pareto fronts and their evolution over iterations.
Seamless Integration
The new architecture allows you to switch between single-objective and multi-objective problems easily, maintaining Opytimizer’s user-friendly interface.
Examples and Documentation
Usage examples for multi-objective problems added in the examples/ directory.
Expanded documentation covering all new features.
⚠️ API Changes / Breaking Changes
Some classes and methods have been refactored to support multiple objectives, which may affect code that relied on internal framework details.
Please review the initialization of functions, spaces, and optimizers to ensure compatibility with this new version.
🛠️ General Improvements
Core refactoring for greater extensibility.
Bug fixes and performance improvements.
Dependency updates.
Thank you to all contributors and users!
For questions, suggestions, or issues, please open an issue on GitHub.