DCDG-EA: Dynamic convergence-diversity guided evolutionary algorithm for many-objective optimization.
Zhiyong LiKe LinMourad NouiouaShilong JiangYu GuPublished in: Expert Syst. Appl. (2019)
Keyphrases
- evolutionary algorithm
- population diversity
- multi objective evolutionary algorithms
- multi objective
- multi objective optimization
- evolutionary computation
- differential evolution
- nsga ii
- optimization problems
- fitness function
- evolutionary process
- genetic algorithm
- simulated annealing
- genetic programming
- pareto dominance
- multiple objectives
- genetic operators
- function optimization
- crossover operator
- dynamic environments
- mutation operator
- evolutionary strategy
- data sets
- optimization method
- information systems
- fitness landscape
- optimization algorithm
- premature convergence
- convergence rate
- global convergence
- quantum evolutionary algorithm
- faster convergence
- dynamically changing
- lower bound
- case study
- website
- machine learning
- neural network