Abs Min Algorithm
The Absolute Minimum (Abs Min) algorithm is a mathematical optimization technique used to find the smallest absolute value of a function within a specified range or interval. This algorithm is particularly useful in solving real-world problems where the focus is on minimizing the magnitude of a certain quantity, regardless of its sign. Applications of the Abs Min algorithm can be found in diverse fields such as engineering, finance, and physics, where it helps to identify optimal solutions to complex problems.
The Abs Min algorithm works by iteratively narrowing down the search interval and converging towards the point that yields the smallest absolute value of the function under consideration. This can be achieved through various approaches such as bisection, golden section search, or the Newton-Raphson method. The choice of the method depends on factors such as the properties of the function, the desired level of accuracy, and the computational resources available. Once the algorithm converges to the optimal point, the minimum absolute value of the function is obtained, providing valuable insights for decision-making and problem-solving in various practical scenarios.
package Mathematics
object AbsMin {
/**
* Method returns Absolute minimum Element from the list
*
* @param listOfElements
* @return
*/
def absMin(elements : List[Int]): Int = abs(elements.minBy(x => abs(x)))
}
