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The proposed Grasshopper Optimisation Algorithm (GOA) mathematically models and mimics the behaviour of grasshopper swarms in nature for solving optimisation problems.
S. Saremi, S. Mirjalili, A. Lewis, Grasshopper Optimisation Algorithm: Theory and Application, Advances in Engineering Software , in press, 2016, DOI: http://dx.doi.org/10.1016/j.advengsoft.2017.01.004
Link: http://www.sciencedirect.com/science/article/pii/S0965997816305646
A Matlab toolbox for this algorithm can be found here: (to be advised later)
If you have no access to the paper, please drop me an email at ali.mirjalili@gmail.com and I will send you the paper.
All of the source codes and extra information as well as more optimization techniques can be found in my personal website at http://www.alimirjalili.com
I have a number of relevant courses in this area. You can enrol via the following links with 95% discount:
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A course on “Optimization Problems and Algorithms: how to understand, formulation, and solve optimization problems”:
https://www.udemy.com/optimisation/?couponCode=MATHWORKSREF
A course on “Introduction to Genetic Algorithms: Theory and Applications”
https://www.udemy.com/geneticalgorithm/?couponCode=MATHWORKSREF
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Cita come
Seyedali Mirjalili (2026). Grasshopper Optimisation Algorithm (GOA) (https://it.mathworks.com/matlabcentral/fileexchange/61421-grasshopper-optimisation-algorithm-goa), MATLAB Central File Exchange. Recuperato .
Riconoscimenti
Ispirato: MOGOA: Multi-Objective Grasshopper Optimization Algorithm
Informazioni generali
- Versione 1.0.0.0 (3,09 MB)
Compatibilità della release di MATLAB
- Compatibile con qualsiasi release
Compatibilità della piattaforma
- Windows
- macOS
- Linux
| Versione | Pubblicato | Note della release | Action |
|---|---|---|---|
| 1.0.0.0 | The errors for test functions F17 and F19 have been fixed. Links added:
|
