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A nondifferentiable optimization approach to ratio-cut partitioning

  • University of Latvia

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Research › peer-review

2 Citations (Scopus)

Abstract

We propose a new method for finding the minimum ratio-cut of a graph. Ratio-cut is NP-hard problem for which the best previously known algorithm gives an O(log n)-factor approximation by solving its dually related maximum concurrent flow problem. We formulate the minimum ratio-cut as a certain nondifferentiable optimization problem, and show that the global minimum of the optimization problem is equal to the minimum ratio-cut. Moreover, we provide strong symbolic computation based evidence that any strict local minimum gives an approximation by a factor of 2. We also give an efficient heuristic algorithm for finding a local minimum of the proposed optimization problem based on standard nondifferentiable optimization methods and evaluate its performance on several families of graphs. We achieve O(n1.6) experimentally obtained running time on these graphs.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsKlaus Jansen, Marian Margraf, Monaldo Mastrolilli, Jose D. P. Rolim
PublisherSpringer Verlag
Pages134-147
Number of pages14
ISBN (Print)3540402055
DOIs
Publication statusPublished - 2003
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2647
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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