PARALLEL MULTISPLITTINGS FOR CONSTRAINED OPTIMIZATION
作者:
H. D. MITTELMANN,
期刊:
Parallel Algorithms and Applications
(Taylor Available online 1996)
卷期:
Volume 9,
issue 1-2
页码: 91-99
ISSN:1063-7192
年代: 1996
DOI:10.1080/10637199608915565
出版商: Taylor & Francis Group
关键词: Parallel algorithms;multisplitting;constrained optimization;D.1.3;G.1.6
数据来源: Taylor
摘要:
The philosophy of multisplitting methods is the replacement of a large-scale linear or nonlinear problem by a set of smaller subproblems, each of which can be solved locally and independently in parallel by taking advantage of well-tested sequential algorithms. Because of this formulation most compute-intensive operations can be calculated independently and the algorithms are highly parallel. In continuation of our earlier work we utilize a new parameter-free formulation of linearly constrained convex minimization problems to obtain a parallel algorithm of multisplitting type. Numerical results both serial and parallel are reported which demonstrate its efficiency and which also show that it compares favorably to our earlier parameter-dependent approach.
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