Abstract
Optimization algorithms exist to find solutions to various problems and then find out the optimal solutions. These algorithms are designed to reach desired goals with high accuracy and low error, as well as improve performance in various fields, including machine learning, operations research, physics, chemistry, and engineering. As technology continues to advance, optimization algorithms are increasingly needed to address complex real-world challenges and drive innovation across all disciplines. Quantitative leaps have been achieved in improving the efficiency of optimization algorithms through the diversity of sources of information feeding these algorithms according to the type of optimization problem, based on scientific and organized foundations. The objectives of this paper are to discuss the most important optimization algorithms, classify the scientific fields involved in their application, and optimize problems involved in this regard, in addition to providing a brief overview for comparison among these algorithms
Recommended Citation
Alridha, Ahmed Hasan; Abd Alsharify, Fouad H.; and Al-Khafaji, Zahir
(2024)
"A Review of Optimization Techniques: Applications and Comparative Analysis,"
Iraqi Journal for Computer Science and Mathematics: Vol. 5:
Iss.
2, Article 5.
DOI: https://doi.org/10.52866/ijcsm.2024-05-02-011
Available at:
https://ijcsm.researchcommons.org/ijcsm/vol5/iss2/5
