A review of the application of the simulated annealing algorithm in structural health monitoring (1995-2021)

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Published Mar 21, 2023
DOI https://doi.org/10.3221/IGF-ESIS.64.04

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Parsa Ghannadi
Department of Civil Engineering, Ahar Branch, Islamic Azad University, Ahar, Iran
Seyed Sina Kourehli
Department of Civil Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran
https://orcid.org/0000-0001-7599-8053 Seyedali Mirjalili
Centre for Artificial Intelligence Research and Optimisation, Torrens University, Adelaide, SA 5000, Australia Yonsei Frontier Lab, Yonsei University, Seoul, South Korea

Abstract

In recent years, many innovative optimization algorithms have been developed. These algorithms have been employed to solve structural damage detection problems as an inverse solution. However, traditional optimization methods such as particle swarm optimization, simulated annealing (SA), and genetic algorithm are constantly employed to detect damages in the structures. This paper reviews the application of  SA in different disciplines of structural health monitoring, such as damage detection, finite element model updating, optimal sensor placement, and system identification. The methodologies, objectives, and results of publications conducted between 1995 and 2021 are analyzed. This paper also provides an in-depth discussion of different open questions and research directions in this area.

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    Issue
    Vol. 17 No. 64 (2023): April 2023
    Section
    Structural Integrity and Durability of Structures

    How to Cite

    Ghannadi, P., Kourehli, S. S. and Mirjalili, S. (2023) “A review of the application of the simulated annealing algorithm in structural health monitoring (1995-2021)”, Frattura ed Integrità Strutturale, 17(64), pp. 51–76. doi: 10.3221/IGF-ESIS.64.04.
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