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

Bahareh Etaati, Amin Abdollahi Dehkordi, Ali Sadollah, Mohammed El-Abd, Mehdi Neshat and Man Fai Leung

Mathematical Problems in Engineering, 2022, vol. 2022, 1-13

Abstract: 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.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:6078986

DOI: 10.1155/2022/6078986

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