A fitness guided mutation operator for improved performance of MOEAs.
Konstantinos MetaxiotisKonstantinos LiagkourasPublished in: ICECS (2013)
Keyphrases
- mutation operator
- evolutionary algorithm
- multi objective optimization
- genetic algorithm
- crossover and mutation
- fitness function
- nsga ii
- multiobjective evolutionary algorithms
- differential evolution
- multi objective
- crossover operator
- premature convergence
- population diversity
- evolutionary programming
- evolutionary computation
- genetic operators
- multi objective evolutionary algorithms
- optimization problems
- evolutionary process
- selection operator
- convergence rate
- search direction
- genetic programming
- function optimization
- simulated annealing
- optimization algorithm
- particle swarm optimization
- convergence speed
- test problems
- crossover and mutation operators
- genetic algorithm ga
- multiobjective evolutionary algorithm
- linear programming
- neural network
- multiscale
- special case
- global search
- hybrid algorithm