YPEA

Yarpiz Evolutionary Algorithms Toolbox (YPEA) is a toolbox to solve optimization problems using Evolutionary Algorithms and Metaheuristics.
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Actualizado 14 dic 2020

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Yarpiz Evolutionary Algorithms Toolbox (YPEA) is a general-purpose toolbox to define and solve optimization problems using Evolutionary Algorithms (EAs) and Metaheuristics. To use this toolbox, you just need to define your optimization problem and then, give the problem to one of the algorithms provided by YPEA, to get it solved.

To get the full source code and help on the toolbox, visit the project repository on GitHub or on the Yarpiz website.
GitHub Repository: https://github.com/smkalami/ypea
Yarpiz: https://yarpiz.com/477/ypea-yarpiz-evolutionary-algorithms

The list of algorithms implemented and provided by the YPEA toolbox is as follows:
1. Artificial Bee Colony (ABC)
2. Ant Colony Optimization for Continuous Domains (ACOR)
3. Bees Algorithm (BA)
4. Biogeography-based Optimization (BBO)
5. Covariance Matrix Adaptation Evolution Strategy (CMA-ES)
6. Cultural Algorithm
7. Differential Evolution (DE)
8. Firefly Algorithm (FA)
9. Genetic Algorithm (GA)
10. Harmony Search (HS)
11. Imperialist Competitive Algorithm (ICA)
12. Invasive Weed Optimization (IWO)
13. Particle Swarm Optimization (PSO)
14. Simulated Annealing (SA)
15. Teaching-Learning-based Optimization (TLBO)

After installing this toolbox, just type 'doc ypea' to get help about how to use the YPEA toolbox.

Citar como

Mostapha Kalami Heris, Yarpiz Evolutionary Algorithms Toolbox for MATLAB (YPEA), Yarpiz, 2020.

Compatibilidad con la versión de MATLAB
Se creó con R2020b
Compatible con cualquier versión desde R2016a
Compatibilidad con las plataformas
Windows macOS Linux

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Versión Publicado Notas de la versión
1.1.0.4

Some minor modifications.

1.1.0.3

Minor modifications in the documentation.

1.1.0.2

Minor modifications in the documentation.

1.1.0.1

Description and image updated.

1.1