AJAS Cover
Frequency: Continuous
ISSN: 1546-9239 (Print)
ISSN: 1554-3641 (Online)
Research Article Open Access

New Approach in Optimization Using Variant of the First Derivative (CFDSM)

Tahseen Ali Jabbar1, Saleh Ismael Najem2 and Sadoun Fahad Dakhil1
  • 1 Fuel and Energy, Technical College of Basrah, Southern Technical University, Basrah, Iraq
  • 2 Mechanical Engineering, Engineering College, University of Basrah, Basrah, Iraq

Abstract

Optimization methods are considered very important in engineering and industrial fields. Many of these methods depend on regression function for finding optimal values. In this research, a new method was adopted based on the change of the signal of the first derivative, where the update is based on the reference of the first derivative of the function. The results show that this method can be used to find optimization, as well as that it is very sensitive to the chosen range.

American Journal of Applied Sciences
Volume 16 No. 10, 2019, 308-313

DOI: https://doi.org/10.3844/ajassp.2019.308.313

Submitted On: 13 July 2018 Published On: 19 December 2019

How to Cite: Jabbar, T. A., Najem, S. I. & Dakhil, S. F. (2019). New Approach in Optimization Using Variant of the First Derivative (CFDSM). American Journal of Applied Sciences, 16(10), 308-313. https://doi.org/10.3844/ajassp.2019.308.313

Open AccessCopyright: © 2019 Tahseen Ali Jabbar, Saleh Ismael Najem and Sadoun Fahad Dakhil. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

  • 3,570 Views
  • 1,358 Downloads
  • 0 Citations

Download

Keywords

  • Optimization
  • Gradient
  • First Derivative