Consider the question of finding the points on the curve xy = 2 closest to the origin. (a) State what function is being minimized for this problem and what the constraint is. Label each. (b) Use Lagrange multipliers to find a system of equations for finding the closest point. Write this system of equations without any vectors. Include the constraint as one of the equations. (c) Solve the system of equations from part (b) to find the points closest on the curve xy² closest to the origin. = 2

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Consider the question of finding the points on the curve xy² = 2 closest to the origin.
(a) State what function is being minimized for this problem and what the constraint is. Label
each.
(b) Use Lagrange multipliers to find a system of equations for finding the closest point. Write this
system of equations without any vectors. Include the constraint as one of the equations.
(c) Solve the system of equations from part (b) to find the points closest on the curve xy² = 2
closest to the origin.
Transcribed Image Text:Consider the question of finding the points on the curve xy² = 2 closest to the origin. (a) State what function is being minimized for this problem and what the constraint is. Label each. (b) Use Lagrange multipliers to find a system of equations for finding the closest point. Write this system of equations without any vectors. Include the constraint as one of the equations. (c) Solve the system of equations from part (b) to find the points closest on the curve xy² = 2 closest to the origin.
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The Lagrange multiplier, λ, measures an increase in the objective function (f(x, y)) through marginal relaxations in the constraint (a rise in k). As a result, the Lagrange multiplier is often referred to as a shadow price.

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