A multi-population differential evolution algorithm based on cellular learning automata and evolutionary context information for optimization in dynamic environments.
Reza VafashoarMohammad Reza MeybodiPublished in: Appl. Soft Comput. (2020)
Keyphrases
- dynamic environments
- global numerical optimization
- genetic algorithm
- multi population
- differential evolution algorithm
- learning automata
- differential evolution
- evolutionary algorithm
- mobile robot
- control parameters
- optimization method
- evolutionary computation
- autonomous agents
- neural network
- fitness function
- simulated annealing
- multi objective
- changing environment
- pursuit algorithm
- hybrid algorithm
- cellular automata
- learning automaton
- optimization problems
- artificial neural networks
- genetic algorithm ga
- metaheuristic
- particle swarm optimization
- reinforcement learning
- population size
- particle swarm
- optimization model
- gene selection
- genetic programming
- feature extraction