Developing a Fast Hybrid Metaheuristic Algorithm to Enhance the Efficiency of Resource-Constrained Applications

 

 

 

Alaa Abdalqahar Jihad1, Ahmed Subhi Abdalkafor2, Sameeh Abdulghafour Jassim3,*

 

1Computer Center, University of Anbar, Anbar, Iraq

 

2College of Computer Science and Information Technology, University of Anbar, Anbar, Iraq

 

3Department of Vocational Education in Anbar, Ministry of Education, Anbar, Iraq

 

3Department of Computer Sciences, College of Science, University of Al Maarif, Al Anbar, 31001, Iraq

 

Emails: it.alaa.heety@uoanbar.edu.iq; ahmed.abdalkafor@uoanbar.edu.iq; sameeh@uoa.edu.iq

 

Text Box: Abstract The rapid development of intelligent computing has led to Internet of Things (IoT) applications and embedded devices suffering from severe constraints on energy, processing, and memory. This calls for fast and lightweight algorithms that maintain performance accuracy without draining resources or affecting response time. This paper presents a new hybrid metaheuristic algorithm that combines the advantages of four optimization algorithms to achieve efficient results and reduce computational complexity without compromising output quality. Experiments demonstrate significant improvements in performance and execution time compared to traditional algorithms, in addition to the algorithm's ability to scale and handle diverse workloads. The lowest improvement of the proposed algorithm compared to other algorithms was approximately 25.7%. This algorithm opens up prospects for effective applications in smart systems in urban and industrial areas.

 

Received: February 25, 2025 Revised: June 05, 2025 Accepted: July 02, 2025

 

Keywords: Metaheuristic Algorithms; Hybrid Algorithms; Resource‑Constrained Applications; Internet of Things (IoT)