The sandpile mutation Genetic Algorithm: an investigation on the working mechanisms of a diversity-oriented and self-organized mutation operator for non-stationary functions.
Carlos M. FernandesJuan Luis Jiménez LaredoAgostinho C. RosaJuan Julián Merelo GuervósPublished in: Appl. Intell. (2013)
Keyphrases
- mutation operator
- non stationary
- genetic algorithm
- premature convergence
- evolutionary algorithm
- differential evolution
- crossover operator
- population diversity
- genetic operators
- evolutionary programming
- crossover and mutation
- fitness function
- function optimization
- convergence rate
- crossover and mutation operators
- adaptive algorithms
- multi objective
- mutation strategy
- initial population
- genetic programming
- evolutionary process
- artificial neural networks
- optimization method
- optimization problems
- simulated annealing
- genetic algorithm ga
- evolutionary strategy
- neural network
- search capabilities
- nsga ii
- population size
- step size
- differential evolution algorithm
- genetic search
- quantum inspired
- lower bound
- optimization algorithm
- particle swarm optimization
- particle swarm