A Numerical Technique for Solving Optimization Problems

Authors

  • Safaa M. Aljassas
  • Ahmed Sabah Al-Jilawi

DOI:

https://doi.org/10.31185/wjps.92

Keywords:

numerical algorithm, Newton's method, nonlinear equations The Hessian matrix, Gradient of a function. numerical algorithm, Newton's method, nonlinear equations The Hessian matrix, Gradient of a function.

Abstract

The aim of this paper is to calculate a better approximation value (whether it is maximize or minimize ) for one- and two-dimensional nonlinear equations using the best numerical optimization algorithms, which is Newton's method. The idea of this technique is based on approximating the function by expanding the Taylor series expansion and iteratively updating the estimate of the optimal solution. we have obtained good results in terms of accuracy and speed of approach, as shown in the examples mentioned. We also mentioned the applications of Newton’s method in multiple disciplines, including engineering, physics, economics, finance, computer graphics, machine learning, image processing, and other applications.

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Published

2023-12-30

Issue

Section

Mathematics

How to Cite

Safaa M. Aljassas, & Ahmed Sabah Al-Jilawi. (2023). A Numerical Technique for Solving Optimization Problems. Wasit Journal for Pure Sciences , 2(4), 1-11. https://doi.org/10.31185/wjps.92