A PARALLEL GENETIC ALGORITHM FOR HEAT CONDUCTION PROBLEMS

ABSTRACT Genetic algorithms are a global optimization method that is ideally suited for implementation on parallel computers. In this article, a genetic algorithm developed to solve problems in heat conduction is parallelized and run on a parallel computer (IBM SP2). The algorithm presented here contains a novel local search operator that greatly improves its accuracy. The algorithm itself and the parallelization strategy are discussed in the first part of the article, followed by a detailed discussion of the algorithm's results and its performance vis-à-vis its serial version.

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