Effects of using two neighborhood structures on the performance of cellular evolutionary algorithms for many-objective optimization.
Hisao IshibuchiYuji SakaneNoritaka TsukamotoYusuke NojimaPublished in: IEEE Congress on Evolutionary Computation (2009)
Keyphrases
- evolutionary algorithm
- multi objective
- multiple objectives
- nsga ii
- optimization problems
- evolutionary computation
- multi objective optimization
- fitness function
- differential evolution algorithm
- cellular automata
- multi objective evolutionary algorithms
- genetic programming
- differential evolution
- simulated annealing
- mutation operator
- constrained optimization problems
- evolution strategy
- evolutionary strategy
- particle swarm optimization
- genetic algorithm
- machine learning
- crossover operator
- genetic algorithm ga
- pareto optimal
- multiobjective optimization
- artificial intelligence