arrow
返回

MEALPY: An open-source library for latest meta-heuristic algorithms in Python

delete2023-06-01
delete108
PRE
AI
T
Thieu, Nguyen Van *
M
Mirjalili, Seyedali
DOI:10.1016/j.sysarc.2023.102871delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
Meta-heuristic algorithms are becoming more prevalent and have been widely applied in various fields. There are numerous reasons for the success of such techniques in both science and industry, including but not limited to simplicity in search/optimization mechanisms, implementation readiness, black-box nature, and ease of use. Although the solutions obtained by such algorithms are not guaranteed to be exactly global optimal, they usually find reasonably good solutions in a reasonable time. Many algorithms have been proposed and developed in the last two decades. However, there is no library implementing meta-heuristic algorithms, which is easy to use and has a vast collection of algorithms. This paper proposes an open-source and cross-platform Python library for nature-inspired optimization algorithms called Mealpy. To propose Mealpy, we analyze the features of existing libraries for meta-heuristic algorithms. After, we propose the designation and the structure of Mealpy and validate it with a case study discussion. Compared with other libraries, our proposed Mealpy has the largest number of classical and state-of-the-art meta-heuristic algorithms, with more than 160 algorithms. Mealpy is an open-source library with well-documented code, has a simple interface, and benefits from minimum dependencies. Mealpy includes a wide range of well-known and recent meta-heuristics algorithms capable of optimizing challenge benchmark functions (e.g. CEC-2017). Mealpy can also be used for practical problems such as optimizing parameters for machine learning models. We invite the research community for widespread evaluations of this comprehensive library as a promising tool for research study and real-world optimization. The source codes, supplementary materials, and guidance is publicly available on GitHub: https://github.com/thieu1995/mealpy.
Keyword:
Meta-heuristic algorithms
Nature-inspired algorithms
Swarm-based computing
Global search optimization
Optimization library
Python software

期刊

Journal of Systems Architecture 封面图
Journal of Systems Architecture
IF:
4.1
论文数:
3.0K
被引数:
4.2K

机构

O
Obuda University
学者数:
655
论文数: 597
被引数: 1.2K
Y
Yonsei University
学者数:
4.8W
论文数: 4.6W
被引数: 5.2W
引用论文

引用论文

Local perfusion of corticosterone in the rat medial hypothalamus potentiates d-fenfluramine-induced elevations of extracellular 5-HT concentrations
err2009-06-01
err0
PREAI
errNa Feng; Martin Telefont; Kyle J. Kelly; Miles Orchinik; Gina L. Forster; Kenneth J. Renner; Christopher A. Lowry
err分享
err收藏
err分享
err收藏
Grey Wolf Optimizer灰狼优化器
err2014-03-01
err1.3W
PREAI
errMirjalili, Seyedali; Mirjalili, Seyed Mohammad; Lewis, Andrew
err分享
err收藏
INFO: An efficient optimization algorithm based on weighted mean of vectorsINFO: 一种基于向量加权均值的高效优化算法
err2022-06-01
err483
PREAI
errAhmadianfar, Iman; Heidari, Ali Asghar; Noshadian, Saeed; Chen, Huiling; Gandomi, Amir H.
err分享
err收藏
err分享
err收藏
Liquid Crystal Elastomers with Magnetic Actuation
err2010-06-08
err0
PREAI
errMoritz Winkler; Andreas Kaiser; Simon Krause; Heino Finkelmann; Annette M. Schmidt
err分享
err收藏
学者 查看更多内容