Sean C. Kugele
ABSTRACT
Engineers increasingly rely on computer simulation to develop new products and to understand emerging technologies. In practice, this process is permeated with uncertainty. Most of the computational tools developed for design optimization ignore or abuse the issue of uncertainty, whereas traditional methods for managing uncertainty are often prohibitively expensive. The ultimate goal of this work is the development of tractable computational tools that address these realities. As a small first step towards this goal, this paper explores the computational cost of multidimensional integration (computing expectation) for robust design optimization.
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Index Terms
- Multidimensional numerical integration for robust design optimization
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