KKT conditions with One Constraint | Examples

For the book, you may refer: amzn.to/3aT4ino
This lecture explains how to solve the nonlinear programming problem with one inequality constraint using Karush-Kuhn-Tucker (KKT) Conditions.
Other lectures:
Part - 2: KKT Conditions with two Constraints: • KKT Conditions with Tw...
Part - 1: KKT Conditions with one Constraint: • KKT conditions with On...
KKT necessary & Sufficient Conditions: • Karush-Kuhn-Tucker Con...
Lagrange Multiplier method with Two constraints: • Lagrange Multiplier Me...
Lagrange Multiplier method with One constraint: • Lagrange Multiplier Me...
Maxima & Minima of the function: • Maxima and Minima of t...
Convex & Concave function: • Convex and Concave Fun...
Hessian Matrix: • Hessian Matrix of a fu...
Quadratic form: • Quadratic form with a ...

[@hayi-ed9mo]

Thank you so much sir 😊🙏 You are a saviour of many students. Keep going sir 🙏🙏

[@NikhilAgrawal-hp7li]

Amazing explanation. You saved me before my exam!

[@danieldekasse4113]

What a tremendous explanation, you're just amazing! thank you dear sir

[@DrHarishGarg]

My pleasure. Keep watching and sharing with others too

[@danieldekasse4113]

@@DrHarishGarg Already done with my classmates

[@danieldekasse4113]

@@DrHarishGarg Dear Sir, I have this kind of objective function to maximize: x + ln(1+y) s.t : px + y ≤ m m>0 I tried the tips that you shared but it doesn’t work. Could you help?

[@anchalmaurya1215]

Thanks sir🙏....u cleared all of my doubts 😊

[@Mammutdej]

This video was absolutely perfect, thank you very much.

[@DrHarishGarg]

My pleasure... Thanks for liking... Keep watching and sharing with others too

[@shubhamyadav360]

I want to maximize xy subject to x+y =0 . And for lembda=0 values of x and y becomes zero and satisfies all the above conditions as you mentioned. So can I stop here and consider my optimal solutions as 0,0 or I proceed further to non zero lembda case.

[@DrHarishGarg]

Dear .. In this NLPP, here you see "xy" is neither a convex nor concave function so it means it is not a convex progranming problem.... Therefore, you have to wolves both cases, lambda =0 and lambda not 0... and after that find which one maximize it.... Remember, if your objective function and constraints both are convex then only one case (where you got the solution) is enough... . i hope it clear you thanks

[@shubhamyadav360]

@@DrHarishGarg Okay Sir, I got it!! Thankyou so much for replying.

[@othmanaljbory3649]

If we have Lagrangian multiples of 5 how to solve 😢

[@MAHESWARJANA-s2h]

Sir, in 2nd example why lambda

[@alekyagujarathi]

13:38 f(x) is concave and g(x) is convex then function should be maximum

[@sandeepgautam7577]

Replace minimum by maximum

[@ketemawdemeke90]

please send about interval quadratic programming

[@hariomgautam882]

your necessary conditions for maximization are wrong as they also depend on value of Gj. I studied that in my college iit madras. U can also watch that lecture on nptelhrd channel.

[@abuhashanmdmashud2036]

nice lecture

[@015priyamvadakumari8]

Nice sir

[@DrHarishGarg]

Thanks and welcome

[@Harish-Dhar-Deewan]

plz explain in hindi

[@ShyamSingh-ui4ih]

0-3:44 bad lecture

[@ShyamSingh-ui4ih]

You don't explain very well sir