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A new metaheuristic algorithm: Shrimp and Goby association search algorithm and its application for damage identification in large-scale and complex structures
A new metaheuristic algorithm: Shrimp and Goby association search algorithm and its application for damage identification in large-scale and complex structures
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Date
2022
Authors
Thanh Sang-To, Hoang Le-Minh, Magd Abdel Wahab, Cuong-Le Thanh
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Research Projects
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Abstract
"largescale
global optimization problems. The performance of SGA is assessed using 13 benchmark high-dimensional
functions, 10 classical benchmark functions, and several real-world engineering applications. For the first time,
an efficient optimization approach for structural health monitoring (SHM) in truss-like structures is presented.
The proposed approach is applied for damage identification of complex structures. A real structure, namely
Canton Tower in Guangzhou, China, is served as an example for damage detection. Interestingly, this tower was
the tallest structure in the world in 2009 with a height of 610 m. The great merit of this example is that it
provides a real complex structure with a high-dimensional problem to assess the performance of SGA in the real
world. The results show that SGA can deal with this problem effectively, at the same time, it operates better to
escape from local optima with faster convergence rate than population-based algorithms."
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Keywords
"SGA,
Damage detection,
High dimension,
Complex structures,
Optimization"