We develop and compare three decomposition algorithms derived from the method of alternating directions. They may be viewed as block Gauss-Seidel variants of augmented Lagrangian approaches that take advantage of block angular structure. From a parallel computation viewpoint, they are ideally suited to a data parallel environment. Numerical results for large-scale multicommodity flow problems are presented to demonstrate the effectiveness of these decomposition algorithms on the Thinking Machines CM-5 parallel supercomputer relative to the widely-used serial optimization package MINOS 5.4.

Alternating Direction Splittings for Block Angular Parallel Optimization

DE LEONE, Renato;
1996

Abstract

We develop and compare three decomposition algorithms derived from the method of alternating directions. They may be viewed as block Gauss-Seidel variants of augmented Lagrangian approaches that take advantage of block angular structure. From a parallel computation viewpoint, they are ideally suited to a data parallel environment. Numerical results for large-scale multicommodity flow problems are presented to demonstrate the effectiveness of these decomposition algorithms on the Thinking Machines CM-5 parallel supercomputer relative to the widely-used serial optimization package MINOS 5.4.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11581/241383
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