Choosing Representation, Mutation, and Crossover in Genetic Algorithms.
Alexander DockhornSimon LucasPublished in: IEEE Comput. Intell. Mag. (2022)
Keyphrases
- genetic algorithm
- evolutionary algorithm
- differential evolution
- crossover operator
- fitness function
- mutation operator
- genetic algorithm ga
- genetic programming
- evolutionary computation
- neural network
- population size
- multi objective
- simulated annealing
- encoding scheme
- function optimization problems
- artificial neural networks
- optimization method
- particle swarm optimization
- genetic operators
- tabu search
- candidate solutions
- representation scheme
- fuzzy logic
- multiscale
- mutation rate
- initial population
- selection strategy
- global search
- feature representation
- search space
- parameter optimization
- convergence rate
- particle swarm optimization pso
- image representation
- natural selection
- binary strings
- optimization algorithm
- metaheuristic