A coordinatewise domain scaling algorithm for M-convex function minimization

Akihisa Tamura

A coordinatewise domain scaling algorithm for M-convex function minimization

Research output: Contribution to journal › Conference article › peer-review

Abstract

We present a polynomial time domain scaling algorithm for the minimization of an M-convex function. M-convex functions are nonlinear discrete functions with (poly)matroid structures, which are being recognized to play a fundamental role in tractable cases of discrete optimization. The novel idea of the algorithm is to use an individual scaling factor for each coordinate.

Original language	English
Pages (from-to)	21-35
Number of pages	15
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2337 LNCS
Publication status	Published - 2002 Dec 1
Externally published	Yes
Event	9th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2002 - Cambridge, MA, United States Duration: 2002 May 27 → 2002 May 29

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

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title = "A coordinatewise domain scaling algorithm for M-convex function minimization",

abstract = "We present a polynomial time domain scaling algorithm for the minimization of an M-convex function. M-convex functions are nonlinear discrete functions with (poly)matroid structures, which are being recognized to play a fundamental role in tractable cases of discrete optimization. The novel idea of the algorithm is to use an individual scaling factor for each coordinate.",

author = "Akihisa Tamura",

year = "2002",

month = dec,

day = "1",

language = "English",

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pages = "21--35",

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AB - We present a polynomial time domain scaling algorithm for the minimization of an M-convex function. M-convex functions are nonlinear discrete functions with (poly)matroid structures, which are being recognized to play a fundamental role in tractable cases of discrete optimization. The novel idea of the algorithm is to use an individual scaling factor for each coordinate.

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M3 - Conference article

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VL - 2337 LNCS

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JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

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T2 - 9th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2002

Y2 - 27 May 2002 through 29 May 2002

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