Penalty Function and Augmented Lagrangian methods 2013

[@adedejiadewumi4943]

Please can You release a tutorial On How To Solve Mixed Constraint Problem with Augumented lAngrangian method

[@nikoskay]

Hi!... I have a simple question. Let's suppose an augmented lagrangian functional.
In these context, the Lagrange multipliers is always an unknown field?. In other words, Can I calculate the primary variable by fixing with a known value the Lagrange multiplier field?
Is there some method to do that?
thanks!

[@louisforlibertarian]

This is an awesome video, and thank you so much! But I have some question on if there are any supplementary techniques that goes from a local optimal point to global optimal point?

[@cvanaret]

you can either:
- multistart local methods, hoping that you'll find a global minimum (albeit with no guarantee)
- use (generally stochastic) metaheuristics, which means you have no guarantee either
- use global methods based on branch and bound, which are the only methods that can guarantee global optimality

[@louisforlibertarian]

@@cvanaret Ok, I got it. Thank you very much!

[@filipmilolipinski5299]

Best explanation of this I have found

[@dmit10]

The best explanation ever! Thanks for sharing it!

[@charry23fercho]

Thank you so much for your effort to share this valuable known and subject. Best regards.

[@vman049]

Excellent video. Very clear.

[@DuyenNguyen-rr9tu]

so touching for an excellent video

[@franciscoabusleme9085]

Perfect explanation, thanks a lot

[@hassanebrahimi5504]

Very helpful. Thanks for the time and effort.

[@hamacababy400]

Thanks Michael! Great video!

[@AJ-et3vf]

Great video. Thank you

[@kyang1305]

Wow finally I understand!!! Thank you so much!

[@beincheekym8]

Thanks for the video, very helpful.

[@SomeRandomDuude]

Perfect! Thank you!

[@AntonMorzhakov]

Спасибо!

[@prashantmahajan1637]

Good 1 thanks for sharing

[@loglosss]

Thanks!

[@jvitor08]

Is good.

[@MichaelZibulevsky]

Thanks!

[@hosseinebrahimian9603]

Tnx! Helpful.

[@apyrase7752]

Super helpful! Thank you :)