A collection of the state-of-the-art MEta-heuristics ALgorithms in PYthon (mealpy)
Project description
A collection of the state-of-the-art MEta-heuristics ALgorithms in PYthon (mealpy)
mealpy
mealpy is a python module for the most of cutting-edge population meta-heuristic algorithms and is distributed under MIT license.
Installation
Dependencies
- Python (>= 3.6)
- Numpy (>= 1.15.1)
User installation
Install the current PyPI release:
pip install mealpy
pip install --upgrade mealpy
Or install the development version from GitHub:
pip install git+https://github.com/thieunguyen5991/mealpy
Example
python examples/simple_run.py
The documentation includes more detailed installation instructions.
Changelog
- See the "ChangeLog.md" for a history of notable changes to mealpy.
Important links
-
Official source code repo: https://github.com/thieunguyen5991/mealpy
-
Download releases: https://pypi.org/project/mealpy/
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Issue tracker: https://github.com/mealpy/mealpy/issues
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This project also related to my another projects which are "meta-heuristics" and "neural-network", check it here
Contributions
Citation
If you use mealpy in your project, I would appreciate citations:
@software{thieu_nguyen_2020_3711949,
author = {Thieu Nguyen},
title = {A collection of the state-of-the-art MEta-heuristics ALgorithms in PYthon: Mealpy},
month = march,
year = 2020,
publisher = {Zenodo},
doi = {10.5281/zenodo.3711948},
url = {https://doi.org/10.5281/zenodo.3711948}
}
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Nguyen, T., Nguyen, T., Nguyen, B. M., & Nguyen, G. (2019). Efficient Time-Series Forecasting Using Neural Network and Opposition-Based Coral Reefs Optimization. International Journal of Computational Intelligence Systems, 12(2), 1144-1161.
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Nguyen, T., Tran, N., Nguyen, B. M., & Nguyen, G. (2018, November). A Resource Usage Prediction System Using Functional-Link and Genetic Algorithm Neural Network for Multivariate Cloud Metrics. In 2018 IEEE 11th Conference on Service-Oriented Computing and Applications (SOCA) (pp. 49-56). IEEE.
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Nguyen, T., Nguyen, B. M., & Nguyen, G. (2019, April). Building Resource Auto-scaler with Functional-Link Neural Network and Adaptive Bacterial Foraging Optimization. In International Conference on Theory and Applications of Models of Computation (pp. 501-517). Springer, Cham.
Documents
| Group | STT | Name | Short | Year | Cite |
|---|---|---|---|---|---|
| Evolutionary | 1 | Genetic Algorithm | GA | 1992 | |
| 2 | Differential Evolution | DE | 1997 | ||
| 3 | |||||
| Swarm | 1 | Particle Swarm Optimization | PSO | 1995 | |
| 2 | Bacterial Foraging Optimization | BFO | 2002 | ||
| 3 | Cat Swarm Optimization | CSO | 2006 | ||
| 4 | Artificial Bee Colony | ABC | 2007 | ||
| 5 | Bat Algorithm | BA | 2010 | ||
| 6 | Social Spider Optimization | SSO | 2013 | ||
| 7 | Grey Wolf Optimizer | GWO | 2014 | ||
| 8 | Social Spider Algorithm | SSA | 2015 | ||
| 9 | Ant Lion Optimizer | ALO | 2015 | ||
| 10 | Moth Flame Optimization | MFO | 2015 | ||
| 11 | Whale Optimization Algorithm | WOA | 2016 | ||
| 12 | Bird Swarm Algorithm | BSA | 2016 | ||
| 13 | Swarm Robotics Search And Rescue | SRSR | 2017 | ||
| 14 | Grasshopper Optimisation Algorithm | GOA | 2017 | ||
| 15 | Earthworm Optimisation Algorithm | EOA | 2018 | ||
| 16 | Moth Search Algorithm | MSA | 2018 | ||
| 17 | Rhino Herd Optimization | RHO | 2018 | ||
| 18 | Emperor Penguin Optimizer | EPO | 2018 | ||
| 19 | Nake Mole-rat Algorithm | NMRA | 2019 | ||
| 20 | Bald Eagle Search | BES | 2019 | ||
| 21 | Pathfinder Algorithm | PFA | 2019 | ||
| 22 | Sailfish Optimizer | SFO | 2019 | ||
| 23 | Harris Hawks Optimization | HHO | 2019 | ||
| 24 | Manta Ray Foraging Optimization | MRFO | 2020 | ||
| 25 | |||||
| Physics | 1 | Wind Driven Optimization | WDO | 2013 | |
| 2 | Multi-Verse Optimizer | MVO | 2016 | ||
| 3 | Tug of War Optimization | TWO | 2016 | ||
| 4 | Electromagnetic Field Optimization | EFO | 2016 |
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