A Comparative State-of-the-Art Constrained Metaheuristics Framework for TRUSS Optimisation on Shape and Sizing

In order to develop the dynamic effectiveness of the structures such as trusses, the application of optimisation methods plays a significant role in improving the shape and size of elements. However, conjoining two heterogeneous variables, nodal coordinates and cross-sectional elements, makes a chal...

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Bibliographic Details
Published in:Mathematical problems in engineering 2022-03, Vol.2022, p.1-13
Main Authors: Etaati, Bahareh, Dehkordi, Amin Abdollahi, Sadollah, Ali, El-Abd, Mohammed, Neshat, Mehdi
Format: Article
Language:English
Subjects:
Case studies
Evolutionary algorithms
Foraging behavior
Genetic algorithms
Heuristic
Heuristic methods
Mathematical programming
Methods
Normal distribution
Optimization
Trusses
Variables
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Summary:In order to develop the dynamic effectiveness of the structures such as trusses, the application of optimisation methods plays a significant role in improving the shape and size of elements. However, conjoining two heterogeneous variables, nodal coordinates and cross-sectional elements, makes a challenging optimisation problem that is nonlinear, multimodal, large-scale with dynamic constraints. To handle these challenges, evolutionary and swarm optimisation algorithms can be robust and practical tools and show great potential to solve such complex problems. This paper proposed a comparative truss optimisation framework to solve two large-scale structures, including 314-bar and 260-bar trusses. The proposed framework consists of twelve state-of-the-art bio-inspired algorithms. The experimental results show that the marine predators algorithm (MPA) performed best compared with other algorithms in terms of convergence speed and the quality of the proposed designs of the trusses.
ISSN:1024-123X
1563-5147
DOI:10.1155/2022/6078986