Applying Information-Gap Decision Theory to a Design Problem Having Severe Uncertainty 2006-01-0273
Often in the early stages of the engineering design process, a decision maker lacks the information needed to represent uncertainty in the input parameters of a performance model. In one particular form of severely deficient information, a nominal estimate is available for an input parameter, but the amount of discrepancy between that estimate and the parameter's true value, as well as the implications of that discrepancy on system performance, are not known. In this paper, the concepts and techniques of information-gap decision theory (IGDT), an established method for making decisions robust to severely deficient information, are examined more closely through application to a design problem with continuous design variables. The uncertain variables in the chosen example problem are parameters of a probability distribution, so the relationship between IGDT and design approaches considering precise and/or imprecise probabilities is explained. Insight gained from a walkthrough of the design example is used to suggest the types of problems an IGDT approach will or will not effectively solve as well as potential limitations that could be encountered when solving more complex problems.
Citation: Duncan, S., Paredis, C., and Bras, B., "Applying Information-Gap Decision Theory to a Design Problem Having Severe Uncertainty," SAE Technical Paper 2006-01-0273, 2006, https://doi.org/10.4271/2006-01-0273. Download Citation
Author(s):
Scott Duncan, Christiaan J. J. Paredis, Bert Bras
Affiliated:
Georgia Institute of Technology
Pages: 14
Event:
SAE 2006 World Congress & Exhibition
ISSN:
0148-7191
e-ISSN:
2688-3627
Also in:
Reliability and Robust Design in Automotive Engineering, 2006-SP-2032, SAE 2006 Transactions Journal of Materials and Manufacturing-V115-5
Related Topics:
Design processes
SAE MOBILUS
Subscribers can view annotate, and download all of SAE's content.
Learn More »