Two-Layers Particle Swarm Optimizer

Hussein Samma; Shahrel Azmin Suandi; Junita Mohamad-Saleh

doi:10.1109/I2CACIS49202.2020.9140204

Two-Layers Particle Swarm Optimizer

Hussein Samma
, Shahrel Azmin Suandi
, Junita Mohamad-Saleh

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

Particle Swarm Optimization (PSO) has been recognized as one of the most widely used algorithms. One limitation of PSO is that it suffers from the problem of premature convergence which makes it easily trapped into local optima regions. To enhance its performances, this work presents a new PSO-based two layers optimizer. One layer is dedicated for performing the task of global search and the second layer is used for local search. Each layer consists of three search operations which are exploration, jump out, and convergence. To assess the performances of the proposed optimizer, CEC2010 large-scale optimization benchmark problems were used in this study. The outcomes indicated that the proposed optimizer outperformed other PSO variant algorithms in both convergence rate and average fitness value.

Original language	English
Title of host publication	2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	165-169
Number of pages	5
ISBN (Electronic)	9781728161334
DOIs	https://doi.org/10.1109/I2CACIS49202.2020.9140204
State	Published - Jun 2020
Externally published	Yes
Event	2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Shah Alam, Malaysia Duration: 20 Jun 2020 → …

Publication series

Name	2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings

Conference

Conference	2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020
Country/Territory	Malaysia
City	Shah Alam
Period	20/06/20 → …

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

Large-scale optimization problems
particle swarm optimizer
two-layers optimizer

ASJC Scopus subject areas

Control and Optimization
Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Engineering (miscellaneous)
Safety, Risk, Reliability and Quality

Access to Document

10.1109/I2CACIS49202.2020.9140204

Cite this

Samma, H., Suandi, S. A., & Mohamad-Saleh, J. (2020). Two-Layers Particle Swarm Optimizer. In 2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings (pp. 165-169). Article 9140204 (2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/I2CACIS49202.2020.9140204

Samma, Hussein ; Suandi, Shahrel Azmin ; Mohamad-Saleh, Junita. / Two-Layers Particle Swarm Optimizer. 2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 165-169 (2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings).

@inproceedings{c930d4fc5dba4588b5db120760b09f24,

title = "Two-Layers Particle Swarm Optimizer",

abstract = "Particle Swarm Optimization (PSO) has been recognized as one of the most widely used algorithms. One limitation of PSO is that it suffers from the problem of premature convergence which makes it easily trapped into local optima regions. To enhance its performances, this work presents a new PSO-based two layers optimizer. One layer is dedicated for performing the task of global search and the second layer is used for local search. Each layer consists of three search operations which are exploration, jump out, and convergence. To assess the performances of the proposed optimizer, CEC2010 large-scale optimization benchmark problems were used in this study. The outcomes indicated that the proposed optimizer outperformed other PSO variant algorithms in both convergence rate and average fitness value.",

keywords = "Large-scale optimization problems, particle swarm optimizer, two-layers optimizer",

author = "Hussein Samma and Suandi, \{Shahrel Azmin\} and Junita Mohamad-Saleh",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 ; Conference date: 20-06-2020",

year = "2020",

month = jun,

doi = "10.1109/I2CACIS49202.2020.9140204",

language = "English",

series = "2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "165--169",

booktitle = "2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings",

address = "United States",

}

Samma, H, Suandi, SA & Mohamad-Saleh, J 2020, Two-Layers Particle Swarm Optimizer. in 2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings., 9140204, 2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 165-169, 2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020, Shah Alam, Malaysia, 20/06/20. https://doi.org/10.1109/I2CACIS49202.2020.9140204

Two-Layers Particle Swarm Optimizer. / Samma, Hussein; Suandi, Shahrel Azmin; Mohamad-Saleh, Junita.
2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. p. 165-169 9140204 (2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Two-Layers Particle Swarm Optimizer

AU - Samma, Hussein

AU - Suandi, Shahrel Azmin

AU - Mohamad-Saleh, Junita

PY - 2020/6

Y1 - 2020/6

N2 - Particle Swarm Optimization (PSO) has been recognized as one of the most widely used algorithms. One limitation of PSO is that it suffers from the problem of premature convergence which makes it easily trapped into local optima regions. To enhance its performances, this work presents a new PSO-based two layers optimizer. One layer is dedicated for performing the task of global search and the second layer is used for local search. Each layer consists of three search operations which are exploration, jump out, and convergence. To assess the performances of the proposed optimizer, CEC2010 large-scale optimization benchmark problems were used in this study. The outcomes indicated that the proposed optimizer outperformed other PSO variant algorithms in both convergence rate and average fitness value.

AB - Particle Swarm Optimization (PSO) has been recognized as one of the most widely used algorithms. One limitation of PSO is that it suffers from the problem of premature convergence which makes it easily trapped into local optima regions. To enhance its performances, this work presents a new PSO-based two layers optimizer. One layer is dedicated for performing the task of global search and the second layer is used for local search. Each layer consists of three search operations which are exploration, jump out, and convergence. To assess the performances of the proposed optimizer, CEC2010 large-scale optimization benchmark problems were used in this study. The outcomes indicated that the proposed optimizer outperformed other PSO variant algorithms in both convergence rate and average fitness value.

KW - Large-scale optimization problems

KW - particle swarm optimizer

KW - two-layers optimizer

UR - https://www.scopus.com/pages/publications/85091895917

U2 - 10.1109/I2CACIS49202.2020.9140204

DO - 10.1109/I2CACIS49202.2020.9140204

M3 - Conference contribution

AN - SCOPUS:85091895917

T3 - 2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings

SP - 165

EP - 169

BT - 2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020

Y2 - 20 June 2020

ER -

Samma H, Suandi SA, Mohamad-Saleh J. Two-Layers Particle Swarm Optimizer. In 2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. p. 165-169. 9140204. (2020 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2020 - Proceedings). doi: 10.1109/I2CACIS49202.2020.9140204

Two-Layers Particle Swarm Optimizer

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this