Guided mutation strategies for multiobjective automotive network architecture.
Martin DohrBernd EichbergerPublished in: IEEE Congress on Evolutionary Computation (2013)
Keyphrases
- multiobjective genetic algorithm
- network architecture
- multi objective
- evolutionary algorithm
- genetic algorithm
- artificial neural
- neural network
- optimization algorithm
- multi objective optimization
- particle swarm optimization
- multiobjective optimization
- neural network model
- network design
- mutation operator
- evolutionary computation
- nsga ii
- differential evolution
- simulated annealing
- multiple objectives
- pareto optimal
- activation function
- crossover operator
- bi objective
- biologically plausible
- conflicting objectives
- optimization problems
- selection operator
- automotive industry
- connection weights
- online auctions
- network infrastructure
- network layer
- artificial bee colony
- genetic algorithm ga
- back propagation
- min max
- service integration
- multiobjective evolutionary algorithm
- uniform design
- multiobjective evolutionary algorithms