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CGO and SNS Optimization Algorithm for the Structures with Discontinuous and Continuous Variables
This study aims to find discontinuous and continuous approaches to reducing the size of planar truss structures with a specified shape and topology. The member's section area has assumed to be a decision variable, and the objective function is to minimize their weight. The member stresses and n...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9747325/ https://www.ncbi.nlm.nih.gov/pubmed/36523266 http://dx.doi.org/10.1155/2022/4211707 |
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author | Ghannadiasl, Amin Zarbilinezhad, Milad |
author_facet | Ghannadiasl, Amin Zarbilinezhad, Milad |
author_sort | Ghannadiasl, Amin |
collection | PubMed |
description | This study aims to find discontinuous and continuous approaches to reducing the size of planar truss structures with a specified shape and topology. The member's section area has assumed to be a decision variable, and the objective function is to minimize their weight. The member stresses and node displacements are the constraints that must maintain within the allowed limits for each condition. Chaos game optimization (CGO) and social network search (SNS) algorithms were used to optimize four well-known planar truss structures. In discontinuous-size cases, the results of the social network search (SNS) algorithm are the most cost-effective. However, the results of the chaos game optimization (CGO) algorithm are the most cost-effective in continuous-size cases. |
format | Online Article Text |
id | pubmed-9747325 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-97473252022-12-14 CGO and SNS Optimization Algorithm for the Structures with Discontinuous and Continuous Variables Ghannadiasl, Amin Zarbilinezhad, Milad Comput Intell Neurosci Research Article This study aims to find discontinuous and continuous approaches to reducing the size of planar truss structures with a specified shape and topology. The member's section area has assumed to be a decision variable, and the objective function is to minimize their weight. The member stresses and node displacements are the constraints that must maintain within the allowed limits for each condition. Chaos game optimization (CGO) and social network search (SNS) algorithms were used to optimize four well-known planar truss structures. In discontinuous-size cases, the results of the social network search (SNS) algorithm are the most cost-effective. However, the results of the chaos game optimization (CGO) algorithm are the most cost-effective in continuous-size cases. Hindawi 2022-12-06 /pmc/articles/PMC9747325/ /pubmed/36523266 http://dx.doi.org/10.1155/2022/4211707 Text en Copyright © 2022 Amin Ghannadiasl and Milad Zarbilinezhad. https://creativecommons.org/licenses/by/4.0/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. |
spellingShingle | Research Article Ghannadiasl, Amin Zarbilinezhad, Milad CGO and SNS Optimization Algorithm for the Structures with Discontinuous and Continuous Variables |
title | CGO and SNS Optimization Algorithm for the Structures with Discontinuous and Continuous Variables |
title_full | CGO and SNS Optimization Algorithm for the Structures with Discontinuous and Continuous Variables |
title_fullStr | CGO and SNS Optimization Algorithm for the Structures with Discontinuous and Continuous Variables |
title_full_unstemmed | CGO and SNS Optimization Algorithm for the Structures with Discontinuous and Continuous Variables |
title_short | CGO and SNS Optimization Algorithm for the Structures with Discontinuous and Continuous Variables |
title_sort | cgo and sns optimization algorithm for the structures with discontinuous and continuous variables |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9747325/ https://www.ncbi.nlm.nih.gov/pubmed/36523266 http://dx.doi.org/10.1155/2022/4211707 |
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