Uncertainty is ubiquitous in engineering design. The past decade has seen a significant growth of research developments in design under uncertainty, and a wide range of applications from designing simple product components to designing complex and emerging engineered systems. While methods like “robust design” and “reliability-based design optimization” have become mature and widely adopted in computational design software, it has become evident that these techniques are mostly limited to handling parametric uncertainty. New methods and strategies for uncertainty characterization, problem formulation, preference elicitation, and risk mitigation are needed for managing many other sources of uncertainty in design such as those associated with modeling and prediction, the design process itself, the product use environment, emergent system behavior, and the changing market.

To address the aforementioned aspects of design under uncertainty, both theoretical and computational challenges need to be overcome. While various approaches exist, some are ad hoc in nature. It is...

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