Noise, sampling, and efficient genetic algorthms
Noise, sampling, and efficient genetic algorthms
Evolutionary Optimization in Dynamic Environments
Evolutionary Optimization in Dynamic Environments
Noisy Local Optimization with Evolution Strategies
Noisy Local Optimization with Evolution Strategies
A Comparison of Evolution Strategies with Other Direct Search Methods in the Presence of Noise
Computational Optimization and Applications
Genetic Algorithms in Noisy Environments
Machine Learning
Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Averaging Efficiently in the Presence of Noise
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Evolution Strategies on Noisy Functions: How to Improve Convergence Properties
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Creating Robust Solutions by Means of Evolutionary Algorithms
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Toward a theory of evolution strategies: Some asymptotical results from the (1,+ λ)-theory
Evolutionary Computation
Scheduling of genetic algorithms in a noisy environment
Evolutionary Computation
Genetic algorithms, selection schemes, and the varying effects of noise
Evolutionary Computation
Genetic algorithms with a robust solution searching scheme
IEEE Transactions on Evolutionary Computation
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
On the limitations of adaptive resampling in using the student's t-test evolution strategies
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
A differential evolution for optimisation in noisy environment
International Journal of Bio-Inspired Computation
The effects of selection on noisy fitness optimization
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Integrating techniques from statistical ranking into evolutionary algorithms
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
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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For noisy optimization problems, there is generally a trade-off between the effort spent to reduce the noise (in order to allow the optimization algorithm to run properly), and the number of solutions evaluated during optimization. However, for stochastic search algorithms like evolutionary optimization, noise is not always a bad thing. On the contrary, in many cases, noise has a very similar effect to the randomness which is purposefully and deliberately introduced e.g. during selection. Using the example of stochastic tournament selection, we show that the noise inherent in the optimization problem should be taken into account by the selection operator, and that one should not reduce noise further than necessary.