Optimizing Industrial Design and Operations - Impacts of Uncertainty
Coporate Research and Technologies, Siemens AG, Germany
Mathematical optimization is still dominated by deterministic models and
corresponding algorithms. But many engineering and industrial optimization
challenges demand for more realistic modelling including stochastic effects.
Common Monte-Carlo methods are too expensive for engineering applications.
Polynomial chaos expansions have found to be an efficient mathematical approach
for several industrial applications, like turbomachinery design and production
Tuesday, April 10, 2012
11:00AM AP&M 2402
Center for Computational Mathematics9500 Gilman Dr. #0112La Jolla, CA 92093-0112Tel: (858)534-9813