| publication name | Implementation of Hardware Genetic Algorithm |
|---|---|
| Authors | Imbaby I. Mahmoud, May Salama, Asmaa Abdel Tawab |
| year | 2008 |
| keywords | |
| journal | |
| volume | Not Available |
| issue | Not Available |
| pages | Not Available |
| publisher | Not Available |
| Local/International | Local |
| Paper Link | Not Available |
| Full paper | download |
| Supplementary materials | Not Available |
Abstract
This work presents a hardware implementation of a Genetic Algorithm. Hardware Genetic Operators are implemented in FPGA. Fitness evaluation, which is problem dependent, is left for implementation as S/W module or problem specific hardware design. This allowed a re-configurable general-purpose design, which is customized by application specific population generation and fitness evaluation solution. A 16 site Random Number Generator module is implemented in VHDL based on Hybrid Cellular Automata (CA). Selection, Crossover, and Mutation Operators are implemented as systolic architecture. For preserving locality & modularity of systolic arrays we separate selection array implementation from the crossover and mutation operators. The chromosomes are fed serially to allow variable length chromosomes. The Genetic Engine is targeted a Xilinx Vertex XC2V2000-5 device using Xilinx Foundation Environment. The simulation is carried out using ModelSim.