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A Decision-Analytic Approach to Reliability-Based Design Optimization

General Motors Technical Center, Warren, Michigan 48090
University of Michigan, Ann Arbor, Michigan 48109
robert.bordley{at}gm.com
pollock{at}umich.edu

Reliability-based design optimization is concerned with designing a product to optimize an objective function, given uncertainties about whether various design constraints will be satisfied. However, the widespread practice of formulating such problems as chance-constrained programs can lead to misleading solutions. While a decision-analytic approach would avoid this undesirable result, many engineers find it difficult to determine the utility functions required for a traditional decision analysis. This paper presents an alternative decision-analytic formulation that, although implicitly using utility functions, is more closely related to probability maximization formulations with which engineers are comfortable and skilled. This result combines the rigor of decision analysis with the convenience of existing optimization approaches.

Subject classifications: decision analysis; stochastic programming; chance-constrained programming.
History: Received April 2007; revision received August 2008; accepted August 2008.