FelooPy: An integrated optimization environment for AutoOR in Python

FelooPy (/fɛlupaɪ/, an abbreviation for feasible, logical, optimal, and Python) is a hyper-optimization interface and an integrated optimization environment (IOE) that provides an all-in-one exact and heuristic optimization tool for AutoOR in Python. The motivation behind the development of FelooPy is to move the focus of operations research scientists from coding to modeling, and from modeling to analysis/analytics to automate time-consuming, iterative tasks of optimization model development, debugging, and implementation. FelooPy can currently give you access to more than 172 single-objective heuristic optimization solvers (thanks to mealpy interface) and 81 single-objective commercial and open-source exact optimization solvers (thanks to pyomo,pulp,ortools, gekko, cplex, gurobi, xpress, picos, pymprog, cvxpy, cylp, linopy, and mip interfaces), all with the same coding syntax! Besides, FelooPy automates common tasks in the optimization process and analytics, by providing tools such as sensitivity analysis, automated encoding/decoding (representation method) for heuristic optimization, timers, and more, all in the Python programming language environment.

Features:

• Free and Open-Source (FOSS) IOE developed under MIT license.
• Easy OR model development workflow.
• All-in-One optimization toolbox.
• Uses single optimization programming syntax for 14 exact and heuristic optimization interfaces in Python.
• Solves an optimization model with 81 exact and 172+5 heuristic optimization solvers (total: 258 optimization algorithms).
• Supports scalable optimization for large-scale real-world problems.
• Supports benchmarking of an optimization problem with various solvers.
• Supports multi-parameter sensitivity analysis on a single objective.
• Supports multi-criteria and multi-objective optimization (coming soon).
• ...

Installation

Note: Installation process requires python>=3.9, pip>=22.3.1 and a stable internet connection.

Terminal command (e.g., CMD or GC):

pip install feloopy==0.2.0

IDE command (e.g., Spyder):

Note: After installation, this line of code should be deleted.

!pip install feloopy==0.2.0

Inside your Python code

Note: After installation, this piece of code should be deleted.

import pip

def install(package):
    if hasattr(pip, 'main'):
        pip.main(['install','-U', package])
    else:
        pip._internal.main(['install','-U', package])

install('feloopy')

From GitHub Releases section

1. Download the feloopy-0.2.0.zip file.
2. Extract it into a specific directory.
3. Open a terminal in that directory.
4. Type: pip install .

From GitHub repository (Prerelease version)

pip install -U git+https://github.com/ktafakkori/feloopy

Documentation

• Tutorial
• Examples
• Exact Solvers
• Heuristic Solvers
• Changelog
• Citation

Contributors

Supporters

This repository will be more and more complete over time. It is kindly requested to support this work by giving a ⭐ to the repository to make it available for a broad range of audiences who are interested in using exact and heuristic optimization techniques in the Python programming language.

Or you might kindly consider consider donations:

• BTC crypto: bc1q37audm2jd75j3rmralxhejtd44yz5az4e2nf4e
• ETH crypto: 0xFceE0143E668c83176b96A20e0c386C54Bc9A6b9
• DOGE crypto: DSu19Ks5KEbFcqvj8QKAL6pCaoiCYAzpAU

Sponsorship

Contact me on Linkedin or Twitter.