Graphical Method in NLPP|Non linear programming problem|Operation Research

👉In this video I have explained about , how to apply GRAPHICAL METHOD in given non linear programming problem.

👉 Few questions covered:
1)How to apply graphical method in non linear programming problem ?

👉About Graphical Solution in NLPP:
In an linear programming problem, the optimal solution was usually at one of the corner points of the convex region generated by the constraints and the objective function of the problem . But it is not necessary to find the solution at a corner or edge of the feasible region of NLPP.

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Vaishali Pant Tiwari

[bharathib]

Akka. Very very thanks. I passed in exam through your videos thsnks fir your work.. im very thankful to you

[natefidalgo]

It amazing we consider linear programming and nonlinear programming a whole subject as the subject in theory can be solved with Lagrange multipliers or in the linear programming case solving system of linear equation (aka linear algebra ) then just checking the feasible regions. The major thing why we have so many algorithms and whole subjects on this branch of optimization theory/operations research topic is efficiency and computability. As the lagrange method is hard to compute exact solutions for and in the linear programming problem case its time consuming to check all possible solutions in a reasonable time to rule which ones are mins/maxs

[natefidalgo]

Nice explanation I am wondering why one cannt just solve all NLPP just by using Lagrange multipliers that one uses from multi-variable calculus and just check the solutions obtained by just substitution and check that there in the feasible regions. After all Lagrange multipliers was meant to solve max/min value problems in several variables with constraint functions. The only difference i can see is that these constraint functions can be inequalities not equalities. But that shouldn't affect finding it for equality then check the inequality region.

[natefidalgo]

But in nice problems that dont have issues of efficiency or computability it reduces to what we have taught high-school students on solving systems of 2 inequalities and maybe solutions to simple nonlinear equations of quadratic nature. In the college years you learn Lagrange multipliers which handles pretty much everything as long as you can compute it reasonable in exact form (which is an issue sometimes). Sure approximations would work to. But its fascinating to see ellipsoid methods, simplex methods, and many others trying to get easier to do this. There all NP in worst case but average case we got some pretty fast stuff.

[rupinderkaur]

Maximize Z=2x+3y subject to constraints XY<8, x^2+y^2<20 and x, y=0 ....plz solve mam

[VijayKumar-iutk]

Likelihood ratio tests, statement of the asymptotic properties of LR statistics with applications (including homogenity means and variances) #madam please do a video of this and upload in youtube please madam i beg u