An adaptive hybrid single-loop method for reliability-based design optimization using iterative control strategy

Jiang, Chen; Qiu, Haobo; Gao, Liang; Cai, Xiwen; Li, Peigen

doi:10.1007/s00158-017-1719-z

Cited by 75 publications

(12 citation statements)

References 41 publications

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“…The calculation of the shifting vector is the key point for the proposed approach and also the fundamental difference from the SORA 17 and its varieties. [18][19][20][21][22][23][24][25][26]32 On one hand, the shifting vector determines the deviation between the actual boundary of the probabilistic constraint and the equivalent boundary of the deterministic constraint in the iterative process. Due to the equivalent boundaries driving the design point to approach the optimal solution, the small deviation between the two boundaries can speed up the convergence.…”

Section: Formulation Of the Proposed Approachmentioning

confidence: 99%

“…The example is a widely used standard test case for RBDO methods [18][19][20][21][22][23][24][25] min…”

Section: A Standard Test Casementioning

confidence: 99%

“…In the sequential optimization and reliability assessment (SORA) proposed by Du et al, 17 the PMA was used to conduct reliability analysis and formulate the approximate equivalent feasible domain of the probabilistic constraints, and whereby the reliability analysis is decoupled from the design optimization. Due to the high efficiency of SORA framework, a series of important variants are further developed to enhance the performance in terms of efficiency, [18][19][20][21][22] accuracy, 23,24 or convergence. [25][26][27] In the above RBDO methods, the efficiency is improved by employing FROM, but the accuracy may be not enough because of the limitation of FORM.…”

Section: Introductionmentioning

confidence: 99%

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A decoupling algorithm with first-order asymptotic integration for reliability-based design optimization

Huang

Yang

2018

Advances in Mechanical Engineering

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Conventional decoupling approaches usually employ first-order reliability method to deal with probabilistic constraints in a reliability-based design optimization problem. In first-order reliability method, constraint functions are transformed into a standard normal space. Extra non-linearity introduced by the non-normal-to-normal transformation may increase the error in reliability analysis and then result in the reliability-based design optimization analysis with insufficient accuracy. In this article, a decoupling approach is proposed to provide an alternative tool for the reliability-based design optimization problems. To improve accuracy, the reliability analysis is performed by first-order asymptotic integration method without any extra non-linearity transformation. To achieve high efficiency, an approximate technique of reliability analysis is given to avoid calculating time-consuming performance function. Two numerical examples and an application of practical laptop structural design are presented to validate the effectiveness of the proposed approach.

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Section: Formulation Of the Proposed Approachmentioning

confidence: 99%

“…The example is a widely used standard test case for RBDO methods [18][19][20][21][22][23][24][25] min…”

Section: A Standard Test Casementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A decoupling algorithm with first-order asymptotic integration for reliability-based design optimization

Huang

Yang

2018

Advances in Mechanical Engineering

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“…Meng et al (2015, 2018a) explored the directional feature of the iterative process and presented an efficient modified chaos control method. Then, a single-loop approach (SLA) is introduced to assess the approximate most probable point (MPP) employing the reliability information of the previous iteration (Jiang et al, 2017). Furthermore, the SLA is combined with chaos control to enhance the stability of the iterative point and applied to solve the reliability-based design problem (Meng and Keshtegar, 2019; Meng et al, 2017, 2018b).…”

Section: Introductionmentioning

confidence: 99%

Chaotic enhanced colliding bodies optimization algorithm for structural reliability analysis

Cheng

Zhao

2019

Advances in Structural Engineering

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It is of extreme importance to assess the failure probability and safety level of structural system in structural design. Nowadays, many researchers presented several approaches for structural reliability analysis, such as the first-order reliability method, Monte Carlo simulation, and the meta-heuristic algorithm. The meta-heuristic algorithm is not only efficient to solve global optimization problems but also shown to be an effective tool for structural reliability analysis. A recent meta-heuristic optimization approach, enhanced colliding bodies optimization, has emerged as a relatively simple implementation with a fast convergence speed. Chaos theory is characterized by its ergodicity, pseudo-randomness, and irregularity. This article thus presents a novel approach introducing chaotic maps into the enhanced colliding bodies optimization algorithm to promote the performance of convergence, named as chaotic enhanced colliding bodies optimization algorithm. The proposed algorithm uses chaotic maps to change the generation pattern of particles and improve convergence characteristics. A procedure based on the effective use of the represented chaotic enhanced colliding bodies optimization is then applied in structural reliability analysis. A variety of numerical and structural problems are tested in this article to demonstrate that the given method actually improves the performance of enhanced colliding bodies optimization in convergence as well as the accuracy for reliability analysis compared with the other methods existing in the literature.

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“…In the literature, sophisticated optimization strategies such as double-loop [34], decoupled-loop [35,36], and single-loop approaches [37,38]…”

Section: Reliability-based Design Optimizationmentioning

confidence: 99%

Heterogeneous Uncertainty Quantification for Reliability-Based Design Optimization

Li¹

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An adaptive hybrid single-loop method for reliability-based design optimization using iterative control strategy

Cited by 75 publications

References 41 publications

A decoupling algorithm with first-order asymptotic integration for reliability-based design optimization

A decoupling algorithm with first-order asymptotic integration for reliability-based design optimization

Chaotic enhanced colliding bodies optimization algorithm for structural reliability analysis

Heterogeneous Uncertainty Quantification for Reliability-Based Design Optimization

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