- #1
harpazo
- 208
- 16
Use Lagrange Multipliers to find the individual extrema, assuming that x and y are positive.
Maximize: f (x, y) = e^(xy)
Constraint: x^2 + y^2 = 8
My Work:
I decided to rewrite the constraint as x^2 + y^2 without the constant 8 as originally given.
g (x, y) = x^2 + y^2
I found the gradient of f to be ye^(xy)i + xe^(xy)j.
I found the gradient of g to be 2xi + 2yj.
I then substituted the above into
gradient of f = L * gradient of g, where L represents the lowercase Greek letter lambda.
ye^(xy)i + xe^(xy)j = L * 2xi + 2yj.
I equated the coefficient of i to 2xL and the coefficient of j to 2yL.
This yields the following system of equations:
ye^(xy) = 2xL
xe^(xy) = 2yL
I am stuck here.
Maximize: f (x, y) = e^(xy)
Constraint: x^2 + y^2 = 8
My Work:
I decided to rewrite the constraint as x^2 + y^2 without the constant 8 as originally given.
g (x, y) = x^2 + y^2
I found the gradient of f to be ye^(xy)i + xe^(xy)j.
I found the gradient of g to be 2xi + 2yj.
I then substituted the above into
gradient of f = L * gradient of g, where L represents the lowercase Greek letter lambda.
ye^(xy)i + xe^(xy)j = L * 2xi + 2yj.
I equated the coefficient of i to 2xL and the coefficient of j to 2yL.
This yields the following system of equations:
ye^(xy) = 2xL
xe^(xy) = 2yL
I am stuck here.