A multi-surrogate multi-tasking genetic algorithm with an adaptive training sample selection strategy for expensive optimization problems.
Huimin ZhuLingyi ShiZhongbo HuQinghua SuPublished in: Eng. Appl. Artif. Intell. (2024)
Keyphrases
- selection strategy
- training samples
- genetic algorithm
- optimization problems
- multi tasking
- evolutionary algorithm
- fitness function
- metaheuristic
- selection strategies
- test sample
- feature space
- operating system
- training set
- supervised learning
- learning algorithm
- objective function
- multi objective
- simulated annealing
- training data
- neural network
- selection algorithm
- genetic algorithm ga
- data mining
- genetic programming
- mutation operation
- artificial neural networks
- optimization algorithm
- high dimensional
- nsga ii
- image processing
- information systems
- computer vision