Optimum Design of truss structures considering nonlinear analysis and dynamic loading using metaheuristic algorithms

Abstract The structural optimization of trusses is a complex problem that can be affected by many different factors. In this research, the authors investigated the optimization of trusses performing a geometric nonlinear analysis under dynamic loading, using two different metaheuristic algorithms: t...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:REM - International Engineering Journal Ročník 78; číslo 1
Hlavní autoři: Domingues, Bárbara Scardini, Rodrigues, Marcos Antônio Campos, Alves, Élcio Cassimiro
Médium: Journal Article
Jazyk:angličtina
Vydáno: Fundação Gorceix 2025
Témata:
dynamic loading
ENGINEERING, MECHANICAL
GEOLOGY
MECHANICS
metaheuristics algorithms
METALLURGY & METALLURGICAL ENGINEERING
nonlinear geometric analysis
optimization
trusses
nonlinear geometric analysis
dynamic loading
optimization
trusses
metaheuristics algorithms
ISSN:2448-167X, 2448-167X
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Abstract The structural optimization of trusses is a complex problem that can be affected by many different factors. In this research, the authors investigated the optimization of trusses performing a geometric nonlinear analysis under dynamic loading, using two different metaheuristic algorithms: the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The objective function was to minimize the weight of the structure. A number of benchmark test problems for spatial trusses considering a geometric nonlinear analysis, and dynamic loading are analyzed to verify the performance of the optimization algorithms. The results showed that both algorithms were able to find efficient solutions to the optimization problem and suggest that the choice of the optimization algorithm can have a significant impact on the performance of the optimization process.
ISSN:2448-167X
2448-167X
DOI:10.1590/0370-44672024780008