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, 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.

• Type: Conference
• Year: 1996
• Where: ICTAI
• Authors: T. L. Lau, Edward P. K. Tsang
• Keywords: Artificial Intelligence, Constraint Optimization Problem, ICTAI 1996, Mutation Based Ga, Processor Configuration Problem