Applying a Mutation-based Genetic Algorithm to Processor Configuration Problems
نویسندگان
چکیده
The Processor Configuration Problem (PCP) is a Constraint Optimization Problem. The task is to link up a finite set of processors into a network, while minimizing the maximum distance between these processors. Since each processor has a limited number of communication channels, a carefully planned layout could minimize the overhead for message switching. In this paper, 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.
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