Larger Offspring Populations Help the (1 + (λ, λ)) Genetic Algorithm to Overcome the Noise.
Alexandra IvanovaDenis AntipovBenjamin DoerrPublished in: CoRR (2023)
Keyphrases
- genetic algorithm
- fitness function
- multi population
- genetic operators
- mutation operator
- crossover and mutation
- crossover operator
- evolutionary algorithm
- noise level
- noisy data
- initial population
- signal to noise ratio
- genetic algorithm ga
- evolution process
- random noise
- neural network
- optimization method
- genetic search
- missing data
- genetic programming
- noise removal
- multi objective
- evolutionary process
- real coded
- memetic algorithm
- fitness landscape
- noise sensitivity
- penalty function
- encoding scheme
- image noise
- objective function
- noise reduction
- differential evolution
- evolutionary computation
- image sequences
- fuzzy logic
- artificial neural networks