Parallel techniques for large-scale nonlinear network optimization
In this paper the technical aspects concerning an efficient implementation of parallel methods for solving large-scale network flow optimization problems are discussed. In particular, the attention will be focused to the evaluation of the numerical performance of different synchronous implementations of the relaxation method on shared-memory multiprocessor system. This method is particularly suited for high-performance computing and is applicable for solving problems with millions of variables which arise in several applications.
KeywordsLarge scale nonlinear network optimization relaxation method complementary slackness coloring shared memory multiprocessor
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