v0.3.7

*) GreyNet implementation. GreyNet is the the rule-engine, that allows true incremental estimation of constraints satisfaction. To understand more, see the docs in greyjack/score_calculation/greynet/docs.
*) A lot of examples for GreyNet
*) GreyNet score calculators for NQueens, CloudBalancing.
*) Note: currently GreyNet is entirely written in Python. I hope, that after reimplementation in Rust, it will completely outperform the pseudo incremental scoring mechanism, especially on really big datasets.
*) Added the ability to stop solving externally (see example in cloud_balancing/)

v0.2.6

*) Optional comparing with global best individual for TabuSearch, LateAcceptance, SimulatedAnnealing

v0.2.5

*) Little fixes for better debugging
*) New examples (Cloud Balancing, Employee Scheduling, etc)

v0.2.3 API for pure (explicit) math problems and much more

MathModel API for modeling optimization problems classic solvers-like. But GreyJack's MathModel is much more general: you can use MathModel not only for LP, QP problems, but for more nonlinear cases (look examples/pure_math/engineering), ML hyper-parameters optimization (look examples) and much more due to MathModel flexibility.

v.0.1.4 Simulated Annealing, refactor, performance increasing

• Simulated Annealing
• Refactor
• Performance increasing (for fast-stepping metaheuristics)

v0.1.1 implementation of an object-oriented approach to constraint solving and optimization, leveraging the power of Polars and Rust

GreyJack Solver v0.1.1
This release marks the realization of a fully functional, object-oriented solving approach, built on the robust foundations of Polars and Rust. The most computationally demanding components have been implemented in Rust, ensuring optimal performance, while seamlessly integrated into a Python interface by maturin and pyo3. While this version delivers the core, fundamental components essential for solving complex problems, future releases will focus on further enhancing functionality, refining the architecture, enhancing user-friendliness (docs, guides, much more examples) and impoving reliability (tests, validation). This milestone represents the heart of the solver, laying the groundwork for what’s to come.