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

Authors :
Shiyuan Yang
Hongtao Wang
Yihe Xu
Yongqiang Guo
Lidong Pan
Jiaming Zhang
Xinkai Guo
Debiao Meng
Jiapeng Wang
Source :
Mathematics, Vol 11, Iss 23, p 4790 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

As engineering systems become increasingly complex, reliability-based design optimization (RBDO) has been extensively studied in recent years and has made great progress. In order to achieve better optimization results, the mathematical model used needs to consider a large number of uncertain factors. Especially when considering mixed uncertainty factors, the contradiction between the large computational cost and the efficiency of the optimization algorithm becomes increasingly fierce. How to quickly find the optimal most probable point (MPP) will be an important research direction of RBDO. To solve this problem, this paper constructs a new RBDO method framework by combining an improved particle swarm algorithm (PSO) with excellent global optimization capabilities and a decoupling strategy using a simulated annealing algorithm (SA). This study improves the efficiency of the RBDO solution by quickly solving MPP points and decoupling optimization strategies. At the same time, the accuracy of RBDO results is ensured by enhancing global optimization capabilities. Finally, this article illustrates the superiority and feasibility of this method through three calculation examples.

Details

Language :
English
ISSN :
22277390
Volume :
11
Issue :
23
Database :
Directory of Open Access Journals
Journal :
Mathematics
Publication Type :
Academic Journal
Accession number :
edsdoj.10db179d13f47f794a46cd34e05d19c
Document Type :
article
Full Text :
https://doi.org/10.3390/math11234790