Absolute Min Algorithm
The Absolute Min Algorithm is a mathematical optimization technique used to find the minimum value of a function within a specified range or interval. This algorithm is particularly useful in situations where the function being optimized is non-linear, non-differentiable, or has multiple local minima. The goal of the Absolute Min Algorithm is to identify the point (or points) within the given interval where the function attains its lowest value, which is called the global minimum.
The algorithm works by iteratively exploring the search space and comparing the function values at different points to find the absolute minimum value. It begins by dividing the search interval into smaller subintervals and evaluating the function at each subinterval's endpoints. The subinterval with the lowest function value is then further divided into smaller subintervals, and this process is repeated until the desired level of precision is achieved or a stopping criterion is met. This way, the algorithm narrows down the search space and converges to the global minimum. The Absolute Min Algorithm is widely used in many fields, including engineering, economics, and computer science, where finding the minimum value of a function is crucial for solving various optimization problems.
package Maths;
import java.util.Arrays;
/**
* description:
* <p>
* absMin([0, 5, 1, 11]) = 0, absMin([3 , -10, -2]) = -2
* </p>
*/
public class AbsoluteMin {
public static void main(String[] args) {
int[] numbers = new int[]{3, -10, -2};
System.out.println("absMin(" + Arrays.toString(numbers) + ") = " + absMin(numbers));
}
/**
* get the value, returns the absolute min value min
*
* @param numbers contains elements
* @return the absolute min value
*/
public static int absMin(int[] numbers) {
int absMinValue = numbers[0];
for (int i = 1, length = numbers.length; i < length; ++i) {
if (Math.abs(numbers[i]) < Math.abs(absMinValue)) {
absMinValue = numbers[i];
}
}
return absMinValue;
}
}
