Applying a mutation-based genetic algorithm to processor configuration problems

The processor configuration problem (PCP) is a constraint optimization problem. The task is to link up a finite set of processors into a network; minimizing the maximum distance between processors. Since each processor has a limited number of communication channels, a carefully planned layout could minimize the overhead for message switching. We present a genetic algorithm (GA) approach to the PCP. Our technique uses a mutation based GA, a function that produces schemata by analyzing previous solutions and an effective data representation. Our approach has been shown to outperform other published techniques in this problem.