Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A Coupled Simulated Annealing and Particle Swarm Optimization Reliability-Based Design Optimization Strategy under Hybrid Uncertainties

Shiyuan Yang
,
Hongtao Wang
,
Yihe Xu
,
Yongqiang Guo
,
Lidong Pan
ORCID logo ,
Jiaming Zhang
,
Xinkai Guo
,
Debiao Meng
* ORCID logo ,
Jiapeng Wang
Version 1 : Received: 23 October 2023 / Approved: 30 October 2023 / Online: 30 October 2023 (07:14:52 CET)

A peer-reviewed article of this Preprint also exists.

Yang, S.; Wang, H.; Xu, Y.; Guo, Y.; Pan, L.; Zhang, J.; Guo, X.; Meng, D.; Wang, J. A Coupled Simulated Annealing and Particle Swarm Optimization Reliability-Based Design Optimization Strategy under Hybrid Uncertainties. Mathematics 2023, 11, 4790. Yang, S.; Wang, H.; Xu, Y.; Guo, Y.; Pan, L.; Zhang, J.; Guo, X.; Meng, D.; Wang, J. A Coupled Simulated Annealing and Particle Swarm Optimization Reliability-Based Design Optimization Strategy under Hybrid Uncertainties. Mathematics 2023, 11, 4790.

Abstract

With the engineering system becoming more and more complex, the uncertainty factors have a more and more profound influence on the reliability and security of the engineering system. In recent years, Reliability-Based Design Optimization (RBDO) has been studied extensively in complex engineering system design. The research on reliability optimization design considering stochastic uncertainty has been comprehensive and widely used. However, the reliability optimization design considering mixed uncertainty has the disadvantages of large computation and imprecise convergence. This study proposes an RBDO method based on Particle Swarm Optimization (PSO) and Simulated Annealing (SA) to overcome this challenge. In the method, PSO is used to solve the most probable point, while SA has excellent global optimization capability to acquire the global optimal solution. Finally, three examples are given to illustrate the advantages of the proposed method.

Keywords

Particle swarm optimization algorithm; Reliability-based design and optimization; Simulated annealing algorithm; Most probable point

Subject

Engineering, Mechanical Engineering

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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