Calculus (3rd Edition)

Published by W. H. Freeman
ISBN 10: 1464125260
ISBN 13: 978-1-46412-526-3

Chapter 15 - Differentiation in Several Variables - 15.8 Lagrange Multipliers: Optimizing with a Constraint - Exercises - Page 832: 24

Answer

Using Theorem 1, we show that the point $\left( {{x_0},{y_0}} \right)$ closest to the origin on the line $ax + by = c$ has coordinates ${x_0} = \frac{{ac}}{{{a^2} + {b^2}}}$, ${\ \ \ }$ ${y_0} = \frac{{bc}}{{{a^2} + {b^2}}}$

Work Step by Step

We are given the line $ax + by = c$. Our task is to minimize the distance $d = \sqrt {{x^2} + {y^2}} $ subject to the constraint $g\left( {x,y} \right) = ax + by - c = 0$. Since finding the minimum distance $d$ is the same as finding the minimum square of the distance ${d^2}$, our task is to minimize $f\left( {x,y} \right) = {x^2} + {y^2}$ subject to the constraint $g\left( {x,y} \right) = ax + by - c = 0$. Step 1. Write out the Lagrange equations Using Theorem 1, the Lagrange condition $\nabla f = \lambda \nabla g$ yields $\left( {2x,2y} \right) = \lambda \left( {a,b} \right)$ So, the Lagrange equations are (1) ${\ \ \ \ }$ $2x = a\lambda $, ${\ \ \ }$ $2y = b\lambda $ Step 2. Solve for $\lambda$ in terms of $x$ and $y$ Since $\left( {0,0} \right)$ does not satisfy the constraint, we may assume that $x \ne 0$ and $y \ne 0$. Thus, $\lambda = \frac{2}{a}x = \frac{2}{b}y$. Step 3. Solve for $x$ and $y$ using the constraint From Step 2 we obtain $y = \frac{b}{a}x$. Substituting it in the constraint gives $ax + b\left( {\frac{b}{a}x} \right) - c = 0$ $x\left( {a + \frac{{{b^2}}}{a}} \right) = c$ So, $x = \frac{{ac}}{{{a^2} + {b^2}}}$. Using $y = \frac{b}{a}x$, we obtain the critical point: $\left( {{x_0},{y_0}} \right) = \left( {\frac{{ac}}{{{a^2} + {b^2}}},\frac{{bc}}{{{a^2} + {b^2}}}} \right)$. This critical point corresponds to the minimum of $f$ subject to the constraint $g\left( {x,y} \right) = ax + by - c = 0$. Step 4. Calculate the critical values We evaluate the minimum value $f\left( {\frac{{ac}}{{{a^2} + {b^2}}},\frac{{bc}}{{{a^2} + {b^2}}}} \right) = \frac{{{c^2}}}{{{a^2} + {b^2}}}$ (the minimum square of the distance). Notice that there is no maximum value since there are points on the line that are arbitrarily far from the origin. Hence, the point $\left( {{x_0},{y_0}} \right)$ closest to the origin on the line $ax + by = c$ has coordinates ${x_0} = \frac{{ac}}{{{a^2} + {b^2}}}$, ${\ \ \ }$ ${y_0} = \frac{{bc}}{{{a^2} + {b^2}}}$
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