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Functions with noise-induced multimodality: a test for evolutionary robust Optimization-properties and performance analysis

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2 Author(s)
H. -G. Beyer ; Res. Center Process & Product Eng., Vorarlberg Univ. of Appl. Sci., Dornbirn, Austria ; B. Sendhoff

This paper proposes and analyzes a class of test functions for evolutionary robust optimization, the "functions with noise-induced multimodality" (FNIMs). After a motivational introduction gleaned from a real-world optimization problem, the robust optimizer properties of this test class are investigated with respect to different robustness measures. The steady-state behavior of evolution strategies on FNIMs will be investigated empirically. Being based on the empirical results, a subclass of FNIMs is identified which is amenable to an asymptotical performance analysis. The results of this analysis will be used to derive recommendations for the choice of strategy-specific parameters such as population size and truncation ratio

Published in:

IEEE Transactions on Evolutionary Computation  (Volume:10 ,  Issue: 5 )