Differential Evolution with Noise Analyzer
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Self-adaptive multimethod search for global optimization in real-parameter spaces
IEEE Transactions on Evolutionary Computation
A differential evolution for optimisation in noisy environment
International Journal of Bio-Inspired Computation
Autonomous experimental design optimization of a flapping wing
Genetic Programming and Evolvable Machines
Using the uncertainty handling CMA-ES for finding robust optima
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Noise analysis compact genetic algorithm
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
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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