A comparison performance analysis of eight meta-heuristic algorithms for optimal design of truss structures with static constraints

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dc.contributor.authorKhodadadi N.
dc.contributor.authorÇiftçioğlu A.Ö.
dc.contributor.authorMirjalili S.
dc.contributor.authorNanni A.
dc.date.accessioned2024-07-22T08:02:18Z
dc.date.available2024-07-22T08:02:18Z
dc.date.issued2023
dc.description.abstractMetaheuristics have been successfully used for solving complex structural optimization problems. Many algorithms are proposed for truss structure size and shape optimization under some constraints. This study considers eight population-based meta-heuristic methods: African Vultures Optimization Algorithm (AVOA), Flow Direction Algorithm (FDA), Arithmetic Optimization Algorithm (AOA), Generalized Normal Distribution Optimization (GNDO), Stochastic Paint Optimizer (SPO), Chaos Game Optimizer (CGO), Crystal Structure Algorithm (CRY) and Material Generation Algorithm (MGO). These meta-heuristics methods are used to optimize the size of three aluminum truss structures. Optimization aims to reduce the weight of the truss members while meeting a set of displacement and stress constraints. The performance of these methods is assessed by solving and optimizing three well-known truss structure benchmarks under some constraints. The results show that the Stochastic Paint Optimizer (SPO) outperforms the other algorithms in terms of accuracy and convergence rate. © 2023
dc.identifier.DOI-ID10.1016/j.dajour.2023.100266
dc.identifier.issn27726622
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/11780
dc.language.isoEnglish
dc.publisherElsevier Inc.
dc.rightsAll Open Access; Gold Open Access
dc.titleA comparison performance analysis of eight meta-heuristic algorithms for optimal design of truss structures with static constraints
dc.typeArticle

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