Estimation of parameters in particle swarm optimization
Abstract
Nowadays the heuristic techniques are becoming one of the most useful tools in solving optimization problems. One of these techniques is Particle Swarm Optimization, PSO algorithm. From the numerical analysis perspective this is a successful method, but many issues are still to be considered regarding the convergence of algorithm. In this paper we deal with the problem of the evaluation of the parameters of the algorithm that assure its convergence. In the previous work we presented some restriction on the parameters of the perturbated dynamical system, that modeled the PSO algorithm. These restrictions are necessary to guarantee the stability of the system. In this paper we present some other restrictions needed to ensure the stability of the system and to advance in the research of the convergence of PSO.
Copyright © 2021 Besiana Cobani, Aurora Simoni, Rigena Sema, Xhensilda Allka. 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.
Cite this article
B. Cobani, A. Simoni, R. Sema, X. Allka, Estimation of parameters in particle swarm optimization, J. Math. Comput. Sci. 11 (2021), 4981–4993. https://doi.org/10.28919/jmcs/5796
BibTeX
@article{Cobani2021,
author = {Cobani, Besiana and Simoni, Aurora and Sema, Rigena and Allka, Xhensilda},
title = {Estimation of parameters in particle swarm optimization},
journal = {J. Math. Comput. Sci.},
volume = {11},
year = {2021},
pages = {4981--4993},
doi = {10.28919/jmcs/5796}
}