A genetic algorithm with randomly shifted gray codes and local optimizations based on quadratic approximations of the fitness.
Alexandre MayerPublished in: GECCO (Companion) (2017)
Keyphrases
- genetic algorithm
- fitness function
- population size
- genetic programming
- crossover and mutation
- evolutionary algorithm
- evolutionary computation
- fitness evaluation
- multi objective
- artificial neural networks
- objective function
- optimization method
- error correction
- genetic operators
- pairwise
- differential evolution
- randomly chosen
- mutation operator
- neural network
- computational complexity
- multi objective optimization
- genetic algorithm ga
- efficient computation
- error correcting codes
- linear functions
- simulated annealing
- upper bound
- job shop scheduling problem
- evolution strategy
- global search
- computationally tractable
- hybrid algorithm