Abstract Evolutionary algorithms are ideal candidates for robust design optimization as they are robust in two different ways. First, their search is robust as the risk of premature convergence is low. Second, their population-based search allows for direct (implicit) extraction of robustness information from the population. This avoids additional computational effort for (explicit) uncertainty quantification. In this work, a standard implicit and a novel approach for robust design optimization based on the CMA-ES are presented. Both approaches are first tested on a test function and then applied to the robust design optimization of a compressor impeller.
Robust Compressor Optimization by Evolutionary Algorithms
2018-07-21
17 pages
Article/Chapter (Book)
Electronic Resource
English
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