بالعربي Non-Dominated Sorting Genetic Algorithm II (NSGA-II) Step-by-Step

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Step-by-step explanation in Arabic of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The tutorial quickly introduces the traditional genetic algorithm for solving single-objective optimization problems and then introduces NSGA-II for solving multi-objective problems. The video explains how non-dominated sorting and crowding distance work using a numerical example.
شرح مبسط خطوة بخطوة عن الخوارزمية الجينية لحل المشاكل متعددة الأهداف.
Get in touch:
Facebook: / ahmed.f.gadd
Twitter: / @ahmedfgad
LinkedIn: / ahmedfgad
For coding the GA in Python, check the PyGAD library.
- Documentation: pygad.readthedocs.io
- GitHub: github.com/ahmedfgad/GeneticA...
- Facebook: / pygad
- Twitter: / @pygadlib
- LinkedIn: / pygad
PyGAD is an open-source Python library for building the genetic algorithm and optimizing machine learning algorithms. It works with Keras and PyTorch. It works with both single-objective and multi-objective optimization problems.

Опубликовано:

12 сен 2023

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Комментарии : 7

@better398 3 дня назад

روعه استاذ

@gkamel9929 5 месяцев назад

Thank U for sharing. Great job

@tfarrag1981 7 месяцев назад

Great dr ahmed

@Hendabdelaziz 6 месяцев назад

جزاك الله خيرا

@amelnaitamer9305 3 месяца назад

Thank you for this video which explains the NSGAII very well, I was not able to understand before despite the different sites and videos that I saw. I have a question, I would like to apply the NSGAII for a problem of placing equipment for which I have dimensions (lengths, widths) on a surface for which I also have the dimension. My goal is to have different combinations of equipment inside the surface. I have as constraint that the equipment does not overlap and that they are all inside the surface. Once I have defined my objective functions and apply the algorithm, how can I visually represent the different equipment placed on the predefined serface? I can't really visualize how this algorithm can provide me differents combinations since NSGA2 is the most popular algorithm in placement problems. Thanks for your help !

@gkamel9929 5 месяцев назад

Sir, the solution G is better in the Feedback than the solution H, E and B. Because the Feedback of G is 4.0 but the others solutions are 4.6, 4.5 and 4.4. So, the solution G is also in the front 2.

@AhmedGadd 5 месяцев назад

Thanks for your comment! But solution G cannot be part of Front 2 because solution C dominates it. Solution C is better than solution G in all the objectives. Note that all the objective functions are minimization. For Cost, solution C has 65 which is better than 80 for G. For Feedback, solution C has 3.5 which is better than 4.5 for G. As solution C is better than solution G in all the objective functions, this means solution C dominates solution G. Thus, solution G cannot be part of Front 2.