*The best explanation and example about multi-objective genetic algorithm on KZread. Does anyone agree with me?*

Thank you. Clicked the first time for me

Amazing!!! I Finally understood the crowding distance. Great explanation Professor. Thanks!!!

@SolvingOptimizationProblems

4 жыл бұрын

Me too

Great lecture , easy to understand the concept and application. Thanks!

Thank you Professor. It was a great lecture.

Thanks for this lecture, helped a lot for my project.

excellent lecture.... it helped me a lot

Thanks profesor...any chance to have a similar lecture for NSGA III ?

Thank you for this video sir , but this video is available in NPTEL list ?? I need more video on cross over probability and mutation probability..?

Great Explanation. Thank You.

Terimakasih banyak prof telah memberi pencerahan dalam pengerjaan tugas akhir saya!

How did r & h value selected in mutation?? are they are random represented for off spring..??

Thanks a lot sir. Very helpful

Thanks , Can i get pdf of this lectuer?

Where is the m-10 and m-11 coming from?

thank you sir you really helped a lot

Thanks profesor.

great lecture!!i almost cry!!! thank you professor!!!!

@ishaanasthana1827

6 ай бұрын

Bhai initial population smjh aayi thi

Thanks, sir!

thank you sir ， that‘s good

Thanks ..sir

Thank you!

u saved me

How to calculate decimal value of r and h from a binary no. Plz explain

@computertutor3951

3 жыл бұрын

Have you got any answer? I am also confused abt that

One question. In case we set the distance of boundary values to infinity while calculating crowding distance, won't we always end up chosing one of the values which has infinite crowding distance?

@caioliberatocalixto

3 жыл бұрын

I was thinking exactly the same. Maybe we could ignore the the function in the case where the point is a boundary and multiply by 2 the other function. So we would be able to compare. But i'm not sure this procedure is correct.

@chinmaypachchhao489

2 жыл бұрын

That's the whole point in assigning it infinity. Those are the least crowded points, so should always be selected to achieve population diversification and avoid local optimization

Can someone explain me how to encode? i know how to convert decimal to binary, but here something different, i talking about generation of initial population at 6:13 and also tell me lecture no. for crossover and mutation. Thanks in advance

@cristobalrivera3439

3 жыл бұрын

I have the same question

@pratibhagond3690

3 жыл бұрын

@@cristobalrivera3439 kzread.info/dash/bejne/l6Rnyq6OdLCdpaQ.html&feature=emb_logo

@pratibhagond3690

3 жыл бұрын

@@cristobalrivera3439 kzread.info/dash/bejne/h46eo8Wyo73fmps.html

@cristobalrivera3439

3 жыл бұрын

@@pratibhagond3690 Thanks !!