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