Feloopy

**What is new?**

* Introducing the `search` class, your all-in-one problem solver!
* Introducing decision environments, allowing for complex modeling and computation tasks and workflows.
* Introducing the improved data toolkit. A class to handle the inputs and outputs of the decision environments.
* Supporting new exact optimization interfaces: `highs`, `insideopt`, and `gams`.
* Supporting multi-objective exact optimization: Normalized weighted sum method (nwsm) and epsilon-constraint method (ecm).
* Supporting multi-parameter sensitivity and similarity analysis.
* Supporting benchmarking interfaces and solvers.
* Introducing a new report interface with clear and structured sections.
* Supporting structured constraint definition.
* Removing bugs and enhancing efficiency.
* Documenting the methods and classes.
* And more!

* This release was experimental for testing the next release.

* **Introducing command line interface tools for easier interaction.**
* **Embedded heuristic optimization algorithms have been revised for better performance.**
* **Full support for multi-attribute decision making has been achieved, thanks to the integration with `pydecision`.**
* **The IIS functionality of supported interfaces has been fixed.**
* **Support for new optimization packages including `niapy` and `pygad` has been added.**
* **Various bugs have been fixed and the user experience has been improved.**
* **Stability and reliability of the software have been enhanced.**
* **Compatibility with newer versions of optimization interfaces has been ensured.**
* **A mathematical model report has been added for better debugging.**
* **A data toolkit has been introduced for data manipulation needs.**
* **The link to interface (lti) method has been introduced for seamless integration.**
* **Performance of the software has been optimized for better speed and efficiency.**
* **This is the most stable release since the introduction of FelooPy.**

Major Enhancements

- **Uncertain Optimization Support**: Can now solve uncertain optimization problems.
- **Improved Reporting**: Generates more detailed reports with additional specifications. These reports can be saved as .txt files for future reference.
- **Better Linearizers Support**: Improved linearizers support, enhancing the overall performance.
- **Single and Multi-objective Optimization**: Full support for both single- and multi-objective optimization problems.
- **New Heuristic Optimization Algorithms**: Supports new heuristic optimization algorithms, providing more options for problem-solving.

User Interface Enhancements

- **Improved Decision/Objective Values Display**: Fixed errors in displaying decisions or objective values, providing a more accurate and intuitive user experience.
- **Improved Report UI**: The user interface for reports has been redesigned and improved, making it easier to understand the output of your optimization problems.

Stability Improvements

- **Fewer Bugs and Better Stability**: Fixed some bugs and improved the overall stability of the software.
- **Enhanced Constraint and Convex Optimization**: Improved the support for constraint and convex optimization, making it more robust and reliable.

Beta Features

- **LocalSolver Support (Beta)**: Testing support for LocalSolver; stay tuned for updates.
- **Pymoo Support (Beta)**: Testing support for Pymoo. Look forward to this feature in upcoming releases.

**Highlights**

- Can solve multi-objective optimization problems.
- Can solve multi-criteria decision making problems.
- Can automatically handle non-linearity for exact optimization.
- Can help define special constraints.
- Provides a better report of the model, its solution processes and the decisions.
- Has fewer bugs and better stability.

- Can solve constraint optimization and convex optimization problems.
- Can define an optimization problem in matrix form.
- Can apply constraint programming techniques.
- Can set solver options, set time limit, show log, number of threads, and save model and log files.
- Can define tensor/matrix variables.
- Can provide a report of the model and the solution process.
- Can report status of solve in heuristic optimization.
- Has fewer bugs and better stability.