The extraordinary particle swarm optimization and its application in constrained engineering problems

Thi Thuy Ngo; Ali Sadollah; Do Guen Yoo; Yeon Moon Choo; Sang Hoon Jun; Joong Hoon Kim

doi:10.1007/978-981-10-3728-3_5

The extraordinary particle swarm optimization and its application in constrained engineering problems

Thi Thuy Ngo, Ali Sadollah, Do Guen Yoo, Yeon Moon Choo, Sang Hoon Jun, Joong Hoon Kim

School of Civil, Environmental and Architectural Engineering

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

1 Citation (Scopus)

Abstract

The particle swarm optimization (PSO) is a natural-inspire optimization algorithm mimicking the movement behavior of animal flocks for food searching. Although the algorithm presents some advantages and widely application, however, there are several drawbacks such as trapping in local optima and immature convergence rate. To overcome these disadvantages, many improved versions of PSO have been proposed. One of the latest variants is the extraordinary particle swarm optimization (EPSO). The particles in the EPSO are assigned to move toward their own determined target through the search space. The applicability of EPSO is verified by several experiments in engineering optimization problems. The application results show the outperformance of the EPSO than the other PSO variants in terms of solution searching and as well as convergence rate.

Original language	English
Title of host publication	Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017)
Editors	Javier Del Ser
Publisher	Springer Verlag
Pages	35-41
Number of pages	7
ISBN (Print)	9789811037276
DOIs	https://doi.org/10.1007/978-981-10-3728-3_5
Publication status	Published - 2017
Event	Proceedings of the 3rd International Conference on Harmony Search Algorithm, ICHSA 2017 - Bilbao, Spain Duration: 2017 Feb 22 → 2017 Feb 24

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	514
ISSN (Print)	2194-5357

Other

Other	Proceedings of the 3rd International Conference on Harmony Search Algorithm, ICHSA 2017
Country/Territory	Spain
City	Bilbao
Period	17/2/22 → 17/2/24

Keywords

Engineering optimization problem
Extraordinary particle swarm optimization
Urban drainage system

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science(all)

Access to Document

10.1007/978-981-10-3728-3_5

Cite this

Ngo, T. T., Sadollah, A., Yoo, D. G., Choo, Y. M., Jun, S. H., & Kim, J. H. (2017). The extraordinary particle swarm optimization and its application in constrained engineering problems. In J. Del Ser (Ed.), Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017) (pp. 35-41). (Advances in Intelligent Systems and Computing; Vol. 514). Springer Verlag. https://doi.org/10.1007/978-981-10-3728-3_5

The extraordinary particle swarm optimization and its application in constrained engineering problems. / Ngo, Thi Thuy; Sadollah, Ali; Yoo, Do Guen; Choo, Yeon Moon; Jun, Sang Hoon; Kim, Joong Hoon.

Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017). ed. / Javier Del Ser. Springer Verlag, 2017. p. 35-41 (Advances in Intelligent Systems and Computing; Vol. 514).

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

Ngo, TT, Sadollah, A, Yoo, DG, Choo, YM, Jun, SH & Kim, JH 2017, The extraordinary particle swarm optimization and its application in constrained engineering problems. in J Del Ser (ed.), Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017). Advances in Intelligent Systems and Computing, vol. 514, Springer Verlag, pp. 35-41, Proceedings of the 3rd International Conference on Harmony Search Algorithm, ICHSA 2017, Bilbao, Spain, 17/2/22. https://doi.org/10.1007/978-981-10-3728-3_5

Ngo TT, Sadollah A, Yoo DG, Choo YM, Jun SH, Kim JH. The extraordinary particle swarm optimization and its application in constrained engineering problems. In Del Ser J, editor, Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017). Springer Verlag. 2017. p. 35-41. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-981-10-3728-3_5

Ngo, Thi Thuy ; Sadollah, Ali ; Yoo, Do Guen ; Choo, Yeon Moon ; Jun, Sang Hoon ; Kim, Joong Hoon. / The extraordinary particle swarm optimization and its application in constrained engineering problems. Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017). editor / Javier Del Ser. Springer Verlag, 2017. pp. 35-41 (Advances in Intelligent Systems and Computing).

@inproceedings{68d1b7e74c774dd9984d83354c33c32b,

title = "The extraordinary particle swarm optimization and its application in constrained engineering problems",

abstract = "The particle swarm optimization (PSO) is a natural-inspire optimization algorithm mimicking the movement behavior of animal flocks for food searching. Although the algorithm presents some advantages and widely application, however, there are several drawbacks such as trapping in local optima and immature convergence rate. To overcome these disadvantages, many improved versions of PSO have been proposed. One of the latest variants is the extraordinary particle swarm optimization (EPSO). The particles in the EPSO are assigned to move toward their own determined target through the search space. The applicability of EPSO is verified by several experiments in engineering optimization problems. The application results show the outperformance of the EPSO than the other PSO variants in terms of solution searching and as well as convergence rate.",

keywords = "Engineering optimization problem, Extraordinary particle swarm optimization, Urban drainage system",

author = "Ngo, {Thi Thuy} and Ali Sadollah and Yoo, {Do Guen} and Choo, {Yeon Moon} and Jun, {Sang Hoon} and Kim, {Joong Hoon}",

note = "Funding Information: This research was supported by a grant (13AWMP-B066744-01) from the Advanced Water Management Research Program funded by the Ministry of Land, Infrastructure, and Transport of the Korean government. Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2017.; Proceedings of the 3rd International Conference on Harmony Search Algorithm, ICHSA 2017 ; Conference date: 22-02-2017 Through 24-02-2017",

year = "2017",

doi = "10.1007/978-981-10-3728-3_5",

language = "English",

isbn = "9789811037276",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Verlag",

pages = "35--41",

editor = "{Del Ser}, Javier",

booktitle = "Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017)",

}

TY - GEN

T1 - The extraordinary particle swarm optimization and its application in constrained engineering problems

AU - Ngo, Thi Thuy

AU - Sadollah, Ali

AU - Yoo, Do Guen

AU - Choo, Yeon Moon

AU - Jun, Sang Hoon

AU - Kim, Joong Hoon

N1 - Funding Information: This research was supported by a grant (13AWMP-B066744-01) from the Advanced Water Management Research Program funded by the Ministry of Land, Infrastructure, and Transport of the Korean government. Publisher Copyright: © Springer Nature Singapore Pte Ltd. 2017.

PY - 2017

Y1 - 2017

N2 - The particle swarm optimization (PSO) is a natural-inspire optimization algorithm mimicking the movement behavior of animal flocks for food searching. Although the algorithm presents some advantages and widely application, however, there are several drawbacks such as trapping in local optima and immature convergence rate. To overcome these disadvantages, many improved versions of PSO have been proposed. One of the latest variants is the extraordinary particle swarm optimization (EPSO). The particles in the EPSO are assigned to move toward their own determined target through the search space. The applicability of EPSO is verified by several experiments in engineering optimization problems. The application results show the outperformance of the EPSO than the other PSO variants in terms of solution searching and as well as convergence rate.

AB - The particle swarm optimization (PSO) is a natural-inspire optimization algorithm mimicking the movement behavior of animal flocks for food searching. Although the algorithm presents some advantages and widely application, however, there are several drawbacks such as trapping in local optima and immature convergence rate. To overcome these disadvantages, many improved versions of PSO have been proposed. One of the latest variants is the extraordinary particle swarm optimization (EPSO). The particles in the EPSO are assigned to move toward their own determined target through the search space. The applicability of EPSO is verified by several experiments in engineering optimization problems. The application results show the outperformance of the EPSO than the other PSO variants in terms of solution searching and as well as convergence rate.

KW - Engineering optimization problem

KW - Extraordinary particle swarm optimization

KW - Urban drainage system

UR - http://www.scopus.com/inward/record.url?scp=85012186663&partnerID=8YFLogxK

U2 - 10.1007/978-981-10-3728-3_5

DO - 10.1007/978-981-10-3728-3_5

M3 - Conference contribution

AN - SCOPUS:85012186663

SN - 9789811037276

T3 - Advances in Intelligent Systems and Computing

SP - 35

EP - 41

BT - Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017)

A2 - Del Ser, Javier

PB - Springer Verlag

T2 - Proceedings of the 3rd International Conference on Harmony Search Algorithm, ICHSA 2017

Y2 - 22 February 2017 through 24 February 2017

ER -

The extraordinary particle swarm optimization and its application in constrained engineering problems

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this