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

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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Tamura, A. (2002). A coordinatewise domain scaling algorithm for M-convex function minimization. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2337 LNCS, 21-35.

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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.",

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