Optimal Mutation and Crossover Rates for a Genetic Algorithm Operating in a Dynamic Environment.
Stephen A. StanhopeJason M. DaidaPublished in: Evolutionary Programming (1998)
Keyphrases
- genetic algorithm
- dynamic environments
- mutation probability
- crossover operator
- evolutionary algorithm
- mutation operator
- genetic algorithm ga
- path planning
- fitness function
- mobile robot
- crossover and mutation
- population size
- differential evolution
- dynamic programming
- genetic operators
- multi objective
- genetic programming
- autonomous agents
- changing environment
- neural network
- simulated annealing
- adaptive control
- function optimization problems
- potential field
- collision avoidance
- real coded
- metaheuristic
- candidate solutions
- artificial neural networks
- messy genetic algorithm
- real environment
- genetic algorithm is employed
- binary decision tree
- simultaneous localization and mapping
- evolutionary process
- selection strategy
- multi objective optimization
- hybrid algorithm