Improving an interior-point algorithm for multicommodity flows by quadratic regularizations

One of the best approaches for some classes of multicommodity flow problems is a specialized interior‐point method that solves the normal equations by a combination of Cholesky factorizations and preconditioned conjugate gradient. Its efficiency depends on the spectral radius—in [0,1)—of a certain m...

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Vydané v:Networks Ročník 59; číslo 1; s. 117 - 131
Hlavní autori: Castro, Jordi, Cuesta, Jordi
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.01.2012
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Abstract One of the best approaches for some classes of multicommodity flow problems is a specialized interior‐point method that solves the normal equations by a combination of Cholesky factorizations and preconditioned conjugate gradient. Its efficiency depends on the spectral radius—in [0,1)—of a certain matrix in the definition of the preconditioner. In a recent work, the authors improved this algorithm (i.e., reduced the spectral radius) for general block‐angular problems by adding a quadratic regularization to the logarithmic barrier. This barrier was shown to be self‐concordant, which guarantees the convergence and polynomial complexity of the algorithm. In this work, we focus on linear multicommodity problems, a particular case of primal block‐angular ones. General results are tailored for multicommodity flows, allowing a local sensitivity analysis on the effect of the regularization. Extensive computational results on some standard and some difficult instances, testing several regularization strategies, are also provided. These results show that the regularized interior‐point algorithm is more efficient than the nonregularized one. From this work it can be concluded that, if interior‐point methods based on conjugate gradients are used, linear multicommodity flow problems are most efficiently solved as a sequence of quadratic ones. © 2011 Wiley Periodicals, Inc. NETWORKS, 2012
AbstractList One of the best approaches for some classes of multicommodity flow problems is a specialized interior‐point method that solves the normal equations by a combination of Cholesky factorizations and preconditioned conjugate gradient. Its efficiency depends on the spectral radius—in [0,1)—of a certain matrix in the definition of the preconditioner. In a recent work, the authors improved this algorithm (i.e., reduced the spectral radius) for general block‐angular problems by adding a quadratic regularization to the logarithmic barrier. This barrier was shown to be self‐concordant, which guarantees the convergence and polynomial complexity of the algorithm. In this work, we focus on linear multicommodity problems, a particular case of primal block‐angular ones. General results are tailored for multicommodity flows, allowing a local sensitivity analysis on the effect of the regularization. Extensive computational results on some standard and some difficult instances, testing several regularization strategies, are also provided. These results show that the regularized interior‐point algorithm is more efficient than the nonregularized one. From this work it can be concluded that, if interior‐point methods based on conjugate gradients are used, linear multicommodity flow problems are most efficiently solved as a sequence of quadratic ones. © 2011 Wiley Periodicals, Inc. NETWORKS, 2012
Author Castro, Jordi
Cuesta, Jordi
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crossref_primary_10_1016_j_amc_2015_08_033
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References_xml – reference: G. H. Golub and C. F. Van Loan, Matrix computations, 3rd edition, Johns Hopkins University Press, Baltimore, 1996.
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– reference: D. Bienstock, Potential function methods for approximately solving linear programming problems. Theory and Practice, Kluwer, Boston, 2002.
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  publication-title: Math Prog
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  end-page: 48
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  year: 2009
  end-page: 409
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  publication-title: Comput Optim Appl
– ident: e_1_2_9_17_2
  doi: 10.1137/S105262340240519X
– ident: e_1_2_9_22_2
  doi: 10.1007/978-1-4419-8853-9
– ident: e_1_2_9_2_2
– ident: e_1_2_9_7_2
  doi: 10.1287/opre.38.2.240
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Snippet One of the best approaches for some classes of multicommodity flow problems is a specialized interior‐point method that solves the normal equations by a...
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SubjectTerms interior-point methods
large-scale computational optimization
multicommodity network flows
preconditioned conjugate gradient
regularizations
Title Improving an interior-point algorithm for multicommodity flows by quadratic regularizations
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