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UBS, 2016, Issue 62, Pages 60–74 (Mi ubs880)  

Analysis and Synthesis of Control Systems

Parallel algorithms with feasible set partitioning for large-scale optimization problems

A. S. Velichko

Institute for Automation and Control Processes of FEB RAS

Abstract: We consider parallel algorithms for the class of constrained optimization problems. The algorithms are based on the two ideas: gradient projection method and decomposition of the set of constraints into disjoint subsets with different number of constraints. The proposed approach is used for a class of large-scale linear programming problems. A number of simulations was made to analyze computational complexity, convergence speed and the parallelization efficiency. The algorithms show a good performance for the special special computationally difficult benchmark problem. The most efficient decomposition strategy is to partition the feasible set into a relatively small number of subsets. The decomposition by separate constraints demonstrates less efficiency of parallelization.

Keywords: parallel algorithm, gradient projection method, decomposition, large-scale problem

Full text: PDF file (248 kB)
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UDC: 519.85
BBK: 22.18
Received: February 1, 2016
Published: July 31, 2016

Citation: A. S. Velichko, “Parallel algorithms with feasible set partitioning for large-scale optimization problems”, UBS, 62 (2016), 60–74

Citation in format AMSBIB
\Bibitem{Vel16}
\by A.~S.~Velichko
\paper Parallel algorithms with feasible set partitioning for large-scale optimization problems
\jour UBS
\yr 2016
\vol 62
\pages 60--74
\mathnet{http://mi.mathnet.ru/ubs880}
\elib{https://elibrary.ru/item.asp?id=26608672}


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