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  4. β-Pareto set prediction for bi-objective reliability-based design optimization
 
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β-Pareto set prediction for bi-objective reliability-based design optimization

Journal
Journal of Mechanical Design
Date Issued
2011
Author(s)
Lin, D.-S.
Ho, C.-M.
Chan, K.-Y.  
DOI
10.1115/1.4004442
URI
http://www.scopus.com/inward/record.url?eid=2-s2.0-79961221507&partnerID=MN8TOARS
https://scholars.lib.ntu.edu.tw/handle/123456789/403684
URL
http://www.scopus.com/inward/record.url?eid=2-s2.0-79961221507&partnerID=MN8TOARS
Abstract
In this research, we investigate design optimization under uncertainties for problems with two objectives. Reliability-based design optimization (RBDO) that considers uncertainties as random variables and/or parameters and formulates constraints probabilistically has received extensive attention. However, research to date has focused primarily on single-objective problems only. We extend RBDO to problems for which multiple objectives are optimized simultaneously. Each constraint reliability value results in a Pareto set. The set of all Pareto frontiers at the various reliability values is denoted as the β-Pareto set. We study the relations between the deterministic Pareto set and the β-Pareto set and then develop a method to systematically determine the exact β-Pareto set of bi-objective linear programming problems. The method is also extended to predict the β-Pareto set of nonlinear problems using the sandwich technique. As a result, we are able to accurately predict the β-Pareto set in the objective space without solving multiple multi-objective optimization problems at various reliability levels. In the early stage of the product design process, the proposed approach can help decision-makers efficiently to determine how product performance varies with reliability level. © 2011 American Society of Mechanical Engineers.
Subjects
bi-objective optimization; design under uncertainty; reliability-based design optimization; Pareto frontiers; decision-making process
Publisher
ASME-AMER SOC MECHANICAL ENG
Type
journal article

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