A Framework for Studying the Effects of Dynamic Crossover, Mutation, and Population Sizing in Genetic Algorithms.
Michael A. LeeHideyuki TakagiPublished in: IEEE/Nagoya-University World Wisepersons Workshop (1994)
Keyphrases
- genetic algorithm
- mutation operator
- evolutionary algorithm
- population size
- initial population
- differential evolution
- crossover and mutation
- candidate solutions
- genetic algorithm ga
- mutation rate
- evolutionary process
- crossover operator
- neural network
- multi objective
- fuzzy logic
- multi population
- genetic operators
- fitness function
- main contribution
- search capabilities
- premature convergence
- evolutionary computation
- metaheuristic
- function optimization
- evolution process
- fitness landscape
- lightweight
- search space
- mutation probability
- adaptive parameter control