A genetic algorithm (GA) can find an optimal solution in many complex problems. GAs have been widely used in many applications. A flexible-very-large-scale integration intellectual property for the GA has been proposed in this paper. This algorithm can dynamically perform various population sizes, fitness lengths, individual lengths, fitness functions, crossover operations, and mutation-rate settings to meet the real-time requirements of various GA applications. It can be seen from the simulation results that our design works very well for the three examples running at an 83-MHz clock frequency.
|Number of pages||7|
|Journal||IEEE Transactions on Instrumentation and Measurement|
|Publication status||Published - 2008 Apr 1|
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering