pfevaluator: A library for evaluating performance metrics of Pareto fronts in multiple/many objective optimization problems

"Knowledge is power, sharing it is the premise of progress in life. It seems like a burden to someone, but it is the only way to achieve immortality." --- Thieu Nguyen

Introduction

Dependencies

• Python (>= 3.6)
• Numpy (>= 1.15.1)
• pygmo (>= 2.13.0)

User installation

Install the current PyPI release:

pip install pfevaluator

Or install the development version from GitHub:

pip install git+https://github.com/thieu1995/pfevaluator

Example

• The more complicated tests in the folder: examples

The documentation includes more detailed installation instructions and explanations.

Changelog

• See the ChangeLog.md for a history of notable changes to permetrics.

Important links

• Official source code repo: https://github.com/thieu1995/pfevaluator

• Official documentation: https://pfevaluator.readthedocs.io/

• Download releases: https://pypi.org/project/pfevaluator/

• Issue tracker: https://github.com/thieu1995/pfevaluator/issues

• This project also related to my another projects which are "meta-heuristics" and "neural-network", check it here

  • https://github.com/thieu1995/opfunu
  • https://github.com/thieu1995/metaheuristics
  • https://github.com/thieu1995/mealpy
  • https://github.com/thieu1995/permetrics
  • https://github.com/chasebk

Contributions

Citation

• If you use permetrics in your project, please cite my works:

@article{nguyen2019efficient,
  title={Efficient Time-Series Forecasting Using Neural Network and Opposition-Based Coral Reefs Optimization},
  author={Nguyen, Thieu and Nguyen, Tu and Nguyen, Binh Minh and Nguyen, Giang},
  journal={International Journal of Computational Intelligence Systems},
  volume={12},
  number={2},
  pages={1144--1161},
  year={2019},
  publisher={Atlantis Press}
}