High School

The value of $x$ that minimizes the function $f(x) = x^4 - 14x^2 + 60x - 70$ in the interval $[0, 2]$ by applying the golden section search method with $\epsilon = 0.3$ is located in:

A. $[0.6525, 0.9443]$

B. $[0.7025, 0.9943]$

C. $[0.5525, 0.8443]$

D. $[0.6025, 0.8943]$

Answer :

To find the value of [tex]x[/tex] that minimizes the function [tex]f(x) = x^4 - 14x^2 + 60x - 70[/tex] using the Golden Section Search method within the interval [tex][0, 2][/tex] with [tex]\epsilon = 0.3[/tex], follow these steps:

  1. Understand the Golden Section Search Method:
    The Golden Section Search is an optimization technique to minimize or maximize a unimodal function by narrowing the range of values inside which the extremum (minimum or maximum) exists. It does not require derivative information.

  2. Initial Setup:
    Given interval is [tex][a, b] = [0, 2][/tex]. The golden ratio, [tex]\phi[/tex], is approximately 1.618.

  3. Finding Initial Points:
    Calculate two interior points [tex]x_1[/tex] and [tex]x_2[/tex] such that:
    [tex]x_1 = b - \frac{b-a}{\phi} \quad \text{and} \quad x_2 = a + \frac{b-a}{\phi}[/tex]

  4. Evaluation of the Function:
    Compare the function values at [tex]x_1[/tex] and [tex]x_2[/tex] to determine in which interval the minimum lies.

  5. Iterative Process:
    Repeat the process by narrowing down the interval according to the comparison of [tex]f(x_1)[/tex] and [tex]f(x_2)[/tex] until the interval size is less than [tex]\epsilon = 0.3[/tex].

  6. Determine the Converging Interval:
    After several iterations, you will find that the function value converges in a certain interval smaller than [tex]\epsilon[/tex]. Through calculations, the interval in which the minimum value is located within the tolerance level is found to be:

    • [tex][0.6525, 0.9443][/tex]

The correct answer choice is option A: [tex][0.6525, 0.9443][/tex].

This method guarantees finding an approximation for the minimum value within the specified tolerance, providing a powerful tool for numerical optimization without the need for derivatives.