The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2016.070809
PDF

FPGA Implementation of Parallel Particle Swarm Optimization Algorithm and Compared with Genetic Algorithm

Author 1: BEN AMEUR Mohamed sadek
Author 2: SAKLY Anis

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 8, 2016.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: In this paper, a digital implementation of Particle Swarm Optimization algorithm (PSO) is developed for implementation on Field Programmable Gate Array (FPGA). PSO is a recent intelligent heuristic search method in which the mechanism of algorithm is inspired by the swarming of biological populations. PSO is similar to the Genetic Algorithm (GA). In fact, both of them use a combination of deterministic and probabilistic rules. The experimental results of this algorithm are effective to evaluate the performance of the PSO compared to GA and other PSO algorithm. New digital solutions are available to generate a hardware implementation of PSO Algorithms. Thus, we developed a hardware architecture based on Finite state machine (FSM) and implemented into FPGA to solve some dispatch computing problems over other circuits based on swarm intelligence. Moreover, the inherent parallelism of these new hardware solutions with a large computational capacity makes the running time negligible regardless the complexity of the processing.

Keywords: PSO algorithm; GA; FPGA; Finite state machine; hardware

BEN AMEUR Mohamed sadek and SAKLY Anis, “FPGA Implementation of Parallel Particle Swarm Optimization Algorithm and Compared with Genetic Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 7(8), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070809

@article{sadek2016,
title = {FPGA Implementation of Parallel Particle Swarm Optimization Algorithm and Compared with Genetic Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070809},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070809},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {8},
author = {BEN AMEUR Mohamed sadek and SAKLY Anis}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org