EvoloPy: An Open-source Nature-inspired Optimization Framework in Python
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Author(s)
Aljarah, Ibrahim
Mirjalili, Seyedali
Castillo, Pedro A
Merelo, Juan J
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Merelo, JJ
Melicio, F
Cadenas, JM
Dourado, A
Madani, K
Ruano, A
Filipe, J
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Porto, PORTUGAL
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.
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Proceedings of the 8th International Joint Conference on Computational Intelligence
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1
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© 2016 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International (CC BY-NC-ND 4.0) License, which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
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Software engineering
Science & Technology
Computer Science, Interdisciplinary Applications
Evolutionary
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Faris, H; Aljarah, I; Mirjalili, S; Castillo, PA; Merelo, JJ, EvoloPy: An Open-source Nature-inspired Optimization Framework in Python, Proceedings of the 8th International Joint Conference on Computational Intelligence, 2016, 1, pp. 171-177