Design Optimization With Discrete and Continuous Variables of Aleatory and Epistemic Uncertainties

Reliability based design optimization has received increasing attention for satisfying high requirements on reliability and safety in structure design. However, in practical engineering design, there are both continuous and discrete design variables. Moreover, both aleatory uncertainty and epistemic uncertainty may associate with design variables. This paper proposes the formulation of random/fuzzy continuous/discrete variables design optimization (RFCDV-DO) and two different approaches for uncertainty analysis (probability/possibility analysis). A method named random/fuzzy sequential optimization and reliability assessment is proposed based on the idea of sequential optimization and reliability assessment to improve efficiency in solving RFCDV-DO problems. An engineering design problem is utilized to demonstrate the approaches and the efficiency of the proposed method.

[1]  M. Rosenblatt Remarks on a Multivariate Transformation , 1952 .

[2]  D. Dubois,et al.  Unfair coins and necessity measures: Towards a possibilistic interpretation of histograms , 1983 .

[3]  John Dalsgaard Sørensen,et al.  Reliability-Based Optimization in Structural Engineering , 1994 .

[4]  Timothy K. Hasselman,et al.  Reliability based structural design optimization for practical applications , 1997 .

[5]  Kemper Lewis,et al.  Collaborative, sequential, and isolated decisions in design , 1997 .

[6]  Kyung K. Choi,et al.  Probabilistic Structural Durability Prediction , 1998 .

[7]  Kyung K. Choi,et al.  A NEW STUDY ON RELIABILITY-BASED DESIGN OPTIMIZATION , 1999 .

[8]  Y.-T. Wu,et al.  Safety-Factor Based Approach for Probability-Based Design Optimization , 2001 .

[9]  Xiaoping Du,et al.  Sequential Optimization and Reliability Assessment Method for Efficient Probabilistic Design , 2004, DAC 2002.

[10]  Kyung K. Choi,et al.  Hybrid Analysis Method for Reliability-Based Design Optimization , 2003 .

[11]  John E. Renaud,et al.  Uncertainty quantification using evidence theory in multidisciplinary design optimization , 2004, Reliab. Eng. Syst. Saf..

[12]  Kyung K. Choi,et al.  A new response surface methodology for reliability-based design optimization , 2004 .

[13]  Kyung K. Choi,et al.  Selecting probabilistic approaches for reliability-based design optimization , 2004 .

[14]  Jun Zhou,et al.  A Design Optimization Method Using Evidence Theory , 2005, DAC 2005.

[15]  B. Youn,et al.  Enriched Performance Measure Approach for Reliability-Based Design Optimization. , 2005 .

[16]  Jun Zhou,et al.  Reliability Estimation and Design with Insufficient Data Based on Possibility Theory , 2004 .

[17]  B. Youn,et al.  Adaptive probability analysis using an enhanced hybrid mean value method , 2005 .

[18]  Kyung K. Choi,et al.  Integration of Reliability- And Possibility-Based Design Optimizations Using Performance Measure Approach , 2005 .

[19]  B. Youn,et al.  Inverse Possibility Analysis Method for Possibility-Based Design Optimization , 2006 .

[20]  Panos Y. Papalambros,et al.  Design Optimization and Reliability Estimation with Incomplete Uncertainty Information , 2006 .

[21]  Byeng D. Youn Adaptive-loop method for non-deterministic design optimization , 2007 .

[22]  K. Choi,et al.  An inverse analysis method for design optimization with both statistical and fuzzy uncertainties , 2008, DAC 2006.