Combining Model-based and Genetics-based Offspring Generation for Multi-objective Optimization Using a Convergence Criterion.
Aimin ZhouYaochu JinQingfu ZhangBernhard SendhoffEdward P. K. TsangPublished in: IEEE Congress on Evolutionary Computation (2006)
Keyphrases
- multi objective optimization
- multi objective
- evolutionary algorithm
- crossover and mutation
- multi objective evolutionary algorithms
- genetic algorithm
- nsga ii
- differential evolution
- multi objective optimization problems
- pareto optimal
- crossover operator
- multiple objectives
- fitness function
- multi objective genetic algorithms
- multi objective genetic algorithm
- convergence speed
- multiple criteria
- genetic operators
- evolutionary computation
- hybrid evolutionary algorithm
- mutation operator
- pareto optimal set
- evolution process
- genetic programming
- convergence rate
- optimization algorithm
- search space
- simulated annealing
- pareto dominance
- neural network
- solving multi objective optimization problems