Extremes of x² + y² on the hyperbola xy = 1

Optimising x^2+y^2 subject to x*y = 1 gives 2 at (-1, -1), with multiplier λ = 2. Full worked solution and an editable calculator.

Optimising f = x^2+y^2 subject to x*y = 1 gives f = 2 at (-1, -1), with λ = 2. Finds the two points on the hyperbola closest to the origin.

The quantity to maximise or minimise

Left-hand side of g = c

Right-hand side

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Frequently asked questions

What is the answer to "Extremes of x² + y² on the hyperbola xy = 1"?

The optimum is f = 2 at (-1, -1), with Lagrange multiplier λ = 2. Finds the two points on the hyperbola closest to the origin.

What system of equations does this produce?

Setting ∇f = λ∇g gives one equation per variable (x, y), plus the constraint x*y = 1. That is 3 equations in 3 unknowns, counting λ.

What does λ mean here?

λ = 2 means that raising the constraint value from 1 by one unit would change the optimal value of f by roughly 2.

About this Calculator

Optimising x^2+y^2 subject to x*y = 1 gives 2 at (-1, -1), with multiplier λ = 2. Full worked solution and an editable calculator.

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