Lagrange Multiplier Method with one constraint

[@taniyamukherjee5159]

Thank you, sir.It is very well explained

[@mohamedalibenaissa6936]

Very helpful ..
Thank you @Dr.Harish Garg

[@DrHarishGarg]

Thanks for watching

[@safurafarheen74]

very helpful video
THANK U SIR

[@DrHarishGarg]

Thanks

[@dr.khalidnaeem6990]

Very well explained!

[@ScienceBronzewall]

For the second to last example can we use the Hessian matrix to determine the max and min of the set of points?

[@suddhasattwakhan8054]

did you get to know the answer?

[@abdulrazakkaladgi6671]

Very nice video, sir last algorithm Roa 3 , is remaining, please make the video.thank you very much

[@ananysinghbaghel9531]

Sir when to use bordered hessian or normal hessian??

[@namratasethia2439]

Sir x,y>= 0 is not part of the discussion .it simply states that you have to have a value greater that or equal to 0. Or we have to consider (0,0) as a point

[@ajoydutta1361]

In the 2 nd problem, H matrix should be 4*4 as m+n= 3 + 1(no of variable + no of constraints)

[@G.T828]

That is only done to find the border hessian, in method 2, you just find the normal hessian of the objective function alone.

[@susindiran9364]

In the last problem, the lagrangian function is f(x) - :\h(x).
There must be a -ve sign instead of +ve sign.

[@snigdhadutta8328]

In the problem just previous the last problem when D4 is calculated for the point (14/5, 0, 14/10; -14/10), the element a33 of Bordered Hessian matrix is not 2(as you show in the screen), it should be -4/5.Then sign of D4 will be positive. It matches neither the condition for maximum or minimum. Then what will be the answer?

[@rahularora1860]

Will it be considered a saddle point?

[@thiru1729]

Hello sir..
We need lecturer notes for Jacobian Method

[@MuhammadIqbal-wu7lv]

Nice Sir,

[@DrHarishGarg]

Keep watching

[@MuhammadIqbal-wu7lv]

@@DrHarishGarg Sure Sir,

[@hey__AJ]

what should we do if answer of one is -ve and another is +ve ......... this will be max or min

[@hey__AJ]

pls give the answer

[@DrHarishGarg]

All the other case which not satisfy the given condition then it is saddle point.

[@preparedfor3957]

Sir what if principal minors of NLP problems are all positive (in my question ∆3 and ∆4 are +ve)????

[@DrHarishGarg]

All other cases which does not met the conditions (as described in the lecture for maxima or minima) is said to be saddle point.

[@sri7606]

❤️

[@Tareq--ri6qe]

❣️

[@ayubayusuf7741]

@abuhanan4807