• Dec 24, 2021 News!Vol 10, No 1- Vol 10, No 2 has been indexed by IET-(Inspec)   [Click]
  • Aug 27, 2020 News!Welcome Prof. D. P. Sharma from India to join the Editorial board of IJFCC     [Click]
  • Aug 18, 2022 News!Vol.11, No.3 has been published with online version.     [Click]
General Information
Editor-in-chief

Prof. Pascal Lorenz
University of Haute Alsace, France
 
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.

IJFCC 2021 Vol.10(3): 29-37 ISSN: 2010-3751
DOI: 10.18178/ijfcc.2021.10.3.576

Convergence Analysis of Particle Swarm Optimization via Illustration Styles

Wei-Der Chang
Abstract—Particle swarm optimization (PSO) is the most important and popular algorithm to solving the engineering optimization problem due to its simple updating formulas and excellent searching capacity. This algorithm is one of evolutionary computations and is also a population-based algorithm. Traditionally, to demonstrate the convergence analysis of the PSO algorithm or its related variations, simulation results in a numerical presentation are often given. This way may be unclear or unsuitable for some particular cases. Hence, this paper will adopt the illustration styles instead of numeric simulation results to more clearly clarify the convergence behavior of the algorithm. In addition, it is well known that three parameters used in the algorithm, i.e., the inertia weight w, position constants c1 and c2, sufficiently dominate the whole searching performance. The influence of these parameter settings on the algorithm convergence will be considered and examined via a simple two-dimensional function optimization problem. All simulation results are displayed using a series of illustrations with respect to various iteration numbers. Finally, some simple rules on how to suitably assign these parameters are also suggested

Index Terms—Particle swarm optimization (PSO), convergence analysis, illustration styles.

W. D. Chang is with the Department of Computer and Communication, Shu-Te University, Kaohsiung, Taiwan (e-mail: wdchang@stu.edu.tw).

[PDF]

Cite: Wei-Der Chang, "Convergence Analysis of Particle Swarm Optimization via Illustration Styles," International Journal of Future Computer and Communication vol. 10, no. 3, pp. 29-37, 2021.

Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Copyright © 2008-2022. International Journal of Future Computer and Communication. All rights reserved.
E-mail: ijfcc@ejournal.net