Two-stage distributed parallel algorithm with message passing interface for maximum flow problem

Maximum flow is one of the important and classical combinatorial optimization problems. However, the time complexity of sequential maximum flow algorithms remains high. In this paper, we present a two-stage distributed parallel algorithm (TSDPA) with message passing interface to improve the computat...

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Bibliographic Details
Published in:The Journal of supercomputing Vol. 71; no. 2; pp. 629 - 647
Main Authors: Jiang, Jincheng, Wu, Lixin
Format: Journal Article
Language:English
Published: Boston Springer US 01.02.2015
Subjects:
Algorithms
Combinatorial analysis
Compilers
Computational efficiency
Computer Science
Estimates
Interpreters
Mathematical analysis
Mathematical models
Message passing
Optimization
Processor Architectures
Programming Languages
Strategy
Message passing interface
Parallel algorithm
Two-stage strategy
Distributed
Maximum flow
ISSN:0920-8542, 1573-0484
Online Access:Get full text
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Summary:Maximum flow is one of the important and classical combinatorial optimization problems. However, the time complexity of sequential maximum flow algorithms remains high. In this paper, we present a two-stage distributed parallel algorithm (TSDPA) with message passing interface to improve the computational performance. The strategy of TSDPA has two stages, which push excess flows separately along cheap and expensive paths identified by a new distance estimate function. In TSDPA, stage 1 enhances the parallel efficiency by omitting high-cost paths and decentralizing calculations, and stage 2 guarantees the achievement of an optimal solution through divide-and-conquer method. The experimental test demonstrates that TSDPA runs 1.2–15.5 times faster than sequential algorithms and is faster than or almost as fast as the H_PRF and Q_PRF codes.
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ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-014-1314-7