An efficient crossover architecture for hardware parallel implementation of genetic algorithm.
Rasoul FarajiHamid Reza NajiPublished in: Neurocomputing (2014)
Keyphrases
- parallel implementation
- genetic algorithm
- parallel architecture
- parallel computers
- parallel computation
- hardware architecture
- real time
- genetic algorithm ga
- processing elements
- embedded processors
- parallel architectures
- hardware implementation
- evolutionary algorithm
- fitness function
- genetic programming
- software implementation
- crossover operator
- mutation operator
- distributed memory
- low cost
- hardware software
- parallel implementations
- vlsi architecture
- genetic operators
- multi objective
- hardware design
- vlsi implementation
- graphics processing units
- hardware and software
- real coded
- crossover and mutation
- selection strategy
- message passing interface
- artificial neural networks
- dedicated hardware
- parallel processing
- simulated annealing
- massively parallel
- computing systems
- differential evolution
- multi objective optimization
- high end
- population size
- particle swarm optimization
- data flow
- parallel genetic algorithm
- embedded systems