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SA-EVPS ALGORITHM FOR DISCRETE SIZE OPTIMIZATION OF THE 582-BAR SPATIAL TRUSS STRUCTURE

Metaheuristic algorithms have become increasingly popular in recent years as a method for determining the optimal design of structures. Nowadays, approximate optimization methods are widely used. This study utilized the Self Adaptive Enhanced Vibrating Particle System (SA-EVPS) algorithm as an appro...

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Main Authors: Paknahad, M., Hosseini, P., Hakim, S.J.S
Format: Article
Language:English
Published: 2023
Subjects:
QA273-280 Probabilities. Mathematical statistics
Online Access:http://eprints.uthm.edu.my/8361/1/J15695_9fd340cc648680cb26b546930eb8a4a7.pdf
http://eprints.uthm.edu.my/8361/
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spelling my.uthm.eprints.83612023-02-22T02:18:08Z http://eprints.uthm.edu.my/8361/ SA-EVPS ALGORITHM FOR DISCRETE SIZE OPTIMIZATION OF THE 582-BAR SPATIAL TRUSS STRUCTURE Paknahad, M. Hosseini, P. Hakim, S.J.S QA273-280 Probabilities. Mathematical statistics Metaheuristic algorithms have become increasingly popular in recent years as a method for determining the optimal design of structures. Nowadays, approximate optimization methods are widely used. This study utilized the Self Adaptive Enhanced Vibrating Particle System (SA-EVPS) algorithm as an approximate optimization method, since the EVPS algorithm requires experimental parameters. As a well-known and large-scale structure, the 582-bar spatial truss structure was analyzed using the finite element method, and optimization processes were implemented using MATLAB. In order to obtain weight optimization, the self-adaptive enhanced vibration particle system (SA-EVPS) is compared with the EVPS algorithm. 2023 Article PeerReviewed text en http://eprints.uthm.edu.my/8361/1/J15695_9fd340cc648680cb26b546930eb8a4a7.pdf Paknahad, M. and Hosseini, P. and Hakim, S.J.S (2023) SA-EVPS ALGORITHM FOR DISCRETE SIZE OPTIMIZATION OF THE 582-BAR SPATIAL TRUSS STRUCTURE. INTERNATIONAL JOURNAL OF OPTIMIZATION IN CIVIL ENGINEERING, 13 (2). pp. 207-217.
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic QA273-280 Probabilities. Mathematical statistics
spellingShingle QA273-280 Probabilities. Mathematical statistics
Paknahad, M.
Hosseini, P.
Hakim, S.J.S
SA-EVPS ALGORITHM FOR DISCRETE SIZE OPTIMIZATION OF THE 582-BAR SPATIAL TRUSS STRUCTURE
description Metaheuristic algorithms have become increasingly popular in recent years as a method for determining the optimal design of structures. Nowadays, approximate optimization methods are widely used. This study utilized the Self Adaptive Enhanced Vibrating Particle System (SA-EVPS) algorithm as an approximate optimization method, since the EVPS algorithm requires experimental parameters. As a well-known and large-scale structure, the 582-bar spatial truss structure was analyzed using the finite element method, and optimization processes were implemented using MATLAB. In order to obtain weight optimization, the self-adaptive enhanced vibration particle system (SA-EVPS) is compared with the EVPS algorithm.
format Article
author Paknahad, M.
Hosseini, P.
Hakim, S.J.S
author_facet Paknahad, M.
Hosseini, P.
Hakim, S.J.S
author_sort Paknahad, M.
title SA-EVPS ALGORITHM FOR DISCRETE SIZE OPTIMIZATION OF THE 582-BAR SPATIAL TRUSS STRUCTURE
title_short SA-EVPS ALGORITHM FOR DISCRETE SIZE OPTIMIZATION OF THE 582-BAR SPATIAL TRUSS STRUCTURE
title_full SA-EVPS ALGORITHM FOR DISCRETE SIZE OPTIMIZATION OF THE 582-BAR SPATIAL TRUSS STRUCTURE
title_fullStr SA-EVPS ALGORITHM FOR DISCRETE SIZE OPTIMIZATION OF THE 582-BAR SPATIAL TRUSS STRUCTURE
title_full_unstemmed SA-EVPS ALGORITHM FOR DISCRETE SIZE OPTIMIZATION OF THE 582-BAR SPATIAL TRUSS STRUCTURE
title_sort sa-evps algorithm for discrete size optimization of the 582-bar spatial truss structure
publishDate 2023
url http://eprints.uthm.edu.my/8361/1/J15695_9fd340cc648680cb26b546930eb8a4a7.pdf
http://eprints.uthm.edu.my/8361/
_version_ 1758580277317206016
score 13.211869

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