Seagull optimization algorithm for solving real-world design optimization problems

Natee Panagant; Nantiwat Pholdee; Sujin Bureerat; Ali Rıza Yıldız; Sadiq M. Sait

doi:10.3139/120.111529

Seagull optimization algorithm for solving real-world design optimization problems

Natee Panagant
, Nantiwat Pholdee
, Sujin Bureerat
, Ali Rıza Yıldız^*
, Sadiq M. Sait

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

98 Scopus citations

Abstract

In this research paper, a new surrogate-assisted metaheuristic for shape optimization is proposed. A seagull optimization algorithm (SOA) is used to solve the shape optimization of a vehicle bracket. The design problem is to find structural shape while minimizing structural mass and meeting a stress constraint. Function evaluations are carried out using finite element analysis and estimated by using a Kriging model. The results show that SOA has outstanding features just as the whale optimization algorithm and salp swarm optimization algorithm for designing optimal components in the industry.

Original language	English
Pages (from-to)	640-644
Number of pages	5
Journal	Materialpruefung/Materials Testing
Volume	62
Issue number	6
DOIs	https://doi.org/10.3139/120.111529
State	Published - Jun 2020

Bibliographical note

Publisher Copyright:
© Carl Hanser Verlag GmbH & Co. KG

Keywords

Control arm
Seagull optimization algorithm
Shape optimization
Structural design

ASJC Scopus subject areas

General Materials Science
Mechanics of Materials
Mechanical Engineering

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10.3139/120.111529

Cite this

@article{79a13a243fd64d5db32b717292c834d5,

title = "Seagull optimization algorithm for solving real-world design optimization problems",

abstract = "In this research paper, a new surrogate-assisted metaheuristic for shape optimization is proposed. A seagull optimization algorithm (SOA) is used to solve the shape optimization of a vehicle bracket. The design problem is to find structural shape while minimizing structural mass and meeting a stress constraint. Function evaluations are carried out using finite element analysis and estimated by using a Kriging model. The results show that SOA has outstanding features just as the whale optimization algorithm and salp swarm optimization algorithm for designing optimal components in the industry.",

keywords = "Control arm, Seagull optimization algorithm, Shape optimization, Structural design",

author = "Natee Panagant and Nantiwat Pholdee and Sujin Bureerat and Yıldız, \{Ali Rıza\} and Sait, \{Sadiq M.\}",

note = "Publisher Copyright: {\textcopyright} Carl Hanser Verlag GmbH \& Co. KG",

year = "2020",

month = jun,

doi = "10.3139/120.111529",

language = "English",

volume = "62",

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T1 - Seagull optimization algorithm for solving real-world design optimization problems

AU - Panagant, Natee

AU - Pholdee, Nantiwat

AU - Bureerat, Sujin

AU - Yıldız, Ali Rıza

AU - Sait, Sadiq M.

N1 - Publisher Copyright: © Carl Hanser Verlag GmbH & Co. KG

PY - 2020/6

Y1 - 2020/6

N2 - In this research paper, a new surrogate-assisted metaheuristic for shape optimization is proposed. A seagull optimization algorithm (SOA) is used to solve the shape optimization of a vehicle bracket. The design problem is to find structural shape while minimizing structural mass and meeting a stress constraint. Function evaluations are carried out using finite element analysis and estimated by using a Kriging model. The results show that SOA has outstanding features just as the whale optimization algorithm and salp swarm optimization algorithm for designing optimal components in the industry.

AB - In this research paper, a new surrogate-assisted metaheuristic for shape optimization is proposed. A seagull optimization algorithm (SOA) is used to solve the shape optimization of a vehicle bracket. The design problem is to find structural shape while minimizing structural mass and meeting a stress constraint. Function evaluations are carried out using finite element analysis and estimated by using a Kriging model. The results show that SOA has outstanding features just as the whale optimization algorithm and salp swarm optimization algorithm for designing optimal components in the industry.

KW - Control arm

KW - Seagull optimization algorithm

KW - Shape optimization

KW - Structural design

UR - https://www.scopus.com/pages/publications/85090589936

U2 - 10.3139/120.111529

DO - 10.3139/120.111529

M3 - Article

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SN - 0025-5300

VL - 62

SP - 640

EP - 644

JO - Materialpruefung/Materials Testing

JF - Materialpruefung/Materials Testing

IS - 6

ER -

Seagull optimization algorithm for solving real-world design optimization problems

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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