Article ID: | iaor200971642 |
Country: | United States |
Volume: | 57 |
Issue: | 5 |
Start Page Number: | 1262 |
End Page Number: | 1270 |
Publication Date: | Sep 2009 |
Journal: | Operations Research |
Authors: | Bordley Robert F, Pollock Stephen M |
Keywords: | quality & reliability, programming: probabilistic |
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.