A New Multidisciplinary Design Optimization Method Accounting for Discrete and Continuous Variables under Aleatory and Epistemic Uncertainties

DOI

10.1080/18756891.2012.670524How to use a DOI?

Keywords

Multidisciplinary design optimization (MDO), Aleatory uncertainty, Epistemic uncertainty, Continuous/discrete variables, Random/Fuzzy/Continuous/Discrete Variables Multidisciplinary Design Optimization (RFCDV-MDO), Sequential Optimization and Reliability Assessment (SORA)

Abstract

Various uncertainties are inevitable in complex engineered systems and must be carefully treated in design activities. Reliability-Based Multidisciplinary Design Optimization (RBMDO) has been receiving increasing attention in the past decades to facilitate designing fully coupled systems but also achieving a desired reliability considering uncertainty. In this paper, a new formulation of multidisciplinary design optimization, namely RFCDV (random/fuzzy/continuous/discrete variables) Multidisciplinary Design Optimization (RFCDV-MDO), is developed within the framework of Sequential Optimization and Reliability Assessment (SORA) to deal with multidisciplinary design problems in which both aleatory and epistemic uncertainties are present. In addition, a hybrid discrete-continuous algorithm is put forth to efficiently solve problems where both discrete and continuous design variables exist. The effectiveness and computational efficiency of the proposed method are demonstrated via a mathematical problem and a pressure vessel design problem.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Hong-Zhong Huang
AU  - Xudong Zhang
AU  - De-Biao Meng
AU  - Yu Liu
AU  - Yan-Feng Li
PY  - 2012
DA  - 2012/02/01
TI  - A New Multidisciplinary Design Optimization Method Accounting for Discrete and Continuous Variables under Aleatory and Epistemic Uncertainties
JO  - International Journal of Computational Intelligence Systems
SP  - 93
EP  - 110
VL  - 5
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2012.670524
DO  - 10.1080/18756891.2012.670524
ID  - Huang2012
ER  -