Lattice polyhedra and submodular flows

Lattice polyhedra, as introduced by Gröflin and Hoffman, form a common framework for various discrete optimization problems. They are specified by a lattice structure on the underlying matrix satisfying certain sub- and supermodularity constraints. Lattice polyhedra provide one of the most general f...

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Published in:Japan journal of industrial and applied mathematics Vol. 29; no. 3; pp. 441 - 451
Main Authors: Fujishige, Satoru, Peis, Britta
Format: Journal Article
Language:English
Published: Japan Springer Japan 01.10.2012
Springer Nature B.V
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ISSN:0916-7005, 1868-937X
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Abstract Lattice polyhedra, as introduced by Gröflin and Hoffman, form a common framework for various discrete optimization problems. They are specified by a lattice structure on the underlying matrix satisfying certain sub- and supermodularity constraints. Lattice polyhedra provide one of the most general frameworks of total dual integral systems. So far no combinatorial algorithm has been found for the corresponding linear optimization problem. We show that the important class of lattice polyhedra in which the underlying lattice is of modular characteristic can be reduced to the Edmonds–Giles polyhedra. Thus, submodular flow algorithms can be applied to this class of lattice polyhedra. In contrast to a previous result of Schrijver, we do not explicitly require that the lattice is distributive. Moreover, our reduction is very simple in that it only uses an arbitrary maximal chain in the lattice.
AbstractList Issue Title: Special Issue on Discrete Structure and Optimization Lattice polyhedra, as introduced by Gröflin and Hoffman, form a common framework for various discrete optimization problems. They are specified by a lattice structure on the underlying matrix satisfying certain sub- and supermodularity constraints. Lattice polyhedra provide one of the most general frameworks of total dual integral systems. So far no combinatorial algorithm has been found for the corresponding linear optimization problem. We show that the important class of lattice polyhedra in which the underlying lattice is of modular characteristic can be reduced to the Edmonds-Giles polyhedra. Thus, submodular flow algorithms can be applied to this class of lattice polyhedra. In contrast to a previous result of Schrijver, we do not explicitly require that the lattice is distributive. Moreover, our reduction is very simple in that it only uses an arbitrary maximal chain in the lattice.[PUBLICATION ABSTRACT]
Lattice polyhedra, as introduced by Gröflin and Hoffman, form a common framework for various discrete optimization problems. They are specified by a lattice structure on the underlying matrix satisfying certain sub- and supermodularity constraints. Lattice polyhedra provide one of the most general frameworks of total dual integral systems. So far no combinatorial algorithm has been found for the corresponding linear optimization problem. We show that the important class of lattice polyhedra in which the underlying lattice is of modular characteristic can be reduced to the Edmonds–Giles polyhedra. Thus, submodular flow algorithms can be applied to this class of lattice polyhedra. In contrast to a previous result of Schrijver, we do not explicitly require that the lattice is distributive. Moreover, our reduction is very simple in that it only uses an arbitrary maximal chain in the lattice.
Author Peis, Britta
Fujishige, Satoru
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Cites_doi 10.1007/s101070050040
10.1147/rd.471.0025
10.1016/S0166-218X(99)00129-8
10.1007/s101070050008
10.1287/moor.23.4.892
10.1016/S0167-5060(08)70734-9
10.1007/s101070100253
10.1007/978-3-642-20807-2_26
10.1016/S0020-0190(00)00052-1
10.1007/s10107-008-0242-9
10.1007/BF02592217
10.1016/B978-0-12-566780-7.50025-8
10.1016/S0927-0507(05)12007-6
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Keywords Edmonds–Giles polyhedra
Distributive lattices
06 (Order, Lattices, Ordered algebraic structures)
Lattice polyhedra
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References_xml – reference: Schrijver, A.: Total dual integrality from directed graphs, crossing families and sub and supermodular functions. In: Pulleyblank, W.R. (ed.) Progress in Combinatorial Optimization, pp. 315–362. Academic Press, Dublin (1984)
– reference: EdmondsJ.GilesR.A min-max relation for submodular functions on graphsAnn. Discrete Math.1977118520446016910.1016/S0167-5060(08)70734-9
– reference: McCormickS.T.FujishigeS.Strongly polynomial and fully combinatorial algorithms for bisubmodular function minimizationMath. Program.20101228712025337541190.6509910.1007/s10107-008-0242-9
– reference: KrügerU.Structural aspects of ordered polymatroidsDiscrete Appl. Math.20009912514817438281016.9007910.1016/S0166-218X(99)00129-8
– reference: FrankA.Increasing the rooted-connectivity of a digraph by oneMath. Program.19998456557616947550930.0507410.1007/s101070050040
– reference: FleischerL.IwataS.McCormickS.T.A faster capacity scaling algorithm for minimum cost submodular flowMath. Program.20029211913918922991046.9007310.1007/s101070100253
– reference: DietrichB.L.HoffmanA.J.On greedy algorithms, partially ordered sets, and submodular functionsIBM J. Res. Dev.2003472530195735010.1147/rd.471.0025
– reference: Fujishige, S.: Submodular functions and optimization, 2nd Edn. In: Annals of Discrete Mathematics, vol. 58. Elsevier, Amsterdam (2005)
– reference: FujishigeS.IwataS.Algorithms for submodular flows. Special issue on algorithm engineering: surveysIEICE Trans. Inf. Syst.2000E83-D322329
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– reference: McCormick, S.T.: Submodular Function Minimization. In: Aardal, K., Nemhauser, G., Weismantel, R. (eds.) Handbook on Discrete Optimization, Chapter 7, pp. 321–391. Elsevier, Amsterdam (2006)
– reference: IwataS.McCormickS.T.ShigenoM.A fast cost scaling algorithm for submodular flowInf. Process. Lett.200074123128176155310.1016/S0020-0190(00)00052-1
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– reference: FaigleU.KernW.Submodular linear programs on forestsMath. Program.19967219520613868340856.90071
– reference: Schrijver, A.: Combinatorial Optimization. Springer, Berlin (2003)
– reference: McCormick, S.T., Peis, B.: A primal-dual algorithm for weighted abstract cut packing. In: Proceeding of the 15th Conference on Integer Programming and Combinatorial Optimization (IPCO 2011). Springer, Berlin (2011)
– reference: Birkhoff, G.: Lattice Theory, vol. 91. American Mathematical Society, Providence (1991)
– reference: FaigleU.KernW.On the core of ordered submodular cost gamesMath. Program.20008748348917575600980.9010310.1007/s101070050008
– reference: FujishigeS.Structures of polyhedra determined by submodular functions on crossing familiesMath. Program.1984291251417454040545.9009710.1007/BF02592217
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Snippet Lattice polyhedra, as introduced by Gröflin and Hoffman, form a common framework for various discrete optimization problems. They are specified by a lattice...
Issue Title: Special Issue on Discrete Structure and Optimization Lattice polyhedra, as introduced by Gröflin and Hoffman, form a common framework for various...
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SubjectTerms Applications of Mathematics
Computational Mathematics and Numerical Analysis
Mathematics
Mathematics and Statistics
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Title Lattice polyhedra and submodular flows
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Volume 29
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