@inproceedings{de35def2816346098d9fe23b5558fdb3,
title = "EvoloPy: An open-source nature-inspired optimization framework in python",
abstract = "EvoloPy is an open source and cross-platform Python framework that implements a wide range of classical and recent nature-inspired metaheuristic algorithms. The goal of this framework is to facilitate the use of metaheuristic algorithms by non-specialists coming from different domains. With a simple interface and minimal dependencies, it is easier for researchers and practitioners to utilize EvoloPy for optimizing and benchmarking their own defined problems using the most powerful metaheuristic optimizers in the literature. This framework facilitates designing new algorithms or improving, hybridizing and analyzing the current ones. The source code of EvoloPy is publicly available at GitHub (https://github.com/7ossam81/EvoloPy).",
keywords = "Evolutionary, Framework, Metaheuristic, Optimization, Python, Swarm optimization",
author = "Hossam Faris and Ibrahim Aljarah and Seyedali Mirjalili and Castillo, {Pedro A.} and Merelo, {Juan J.}",
year = "2016",
month = jan,
day = "1",
language = "English",
series = "IJCCI 2016 - Proceedings of the 8th International Joint Conference on Computational Intelligence",
publisher = "SciTePress",
pages = "171--177",
editor = "Merelo, {Juan Julian} and Cadenas, {Jose M.} and Fernando Melicio and Antonio Dourado and Antonio Ruano and Joaquim Filipe and Kurosh Madani",
booktitle = "ECTA 2016 - 8th International Conference on Evolutionary Computation Theory and Applications",
note = "8th International Joint Conference on Computational Intelligence, IJCCI 2016 ; Conference date: 09-11-2016 Through 11-11-2016",
}