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Faster Algorithms for Next Breakpoint and Max Value for Parametric Global Minimum Cuts

Aissi, Hassene; McCormick, S. Thomas; Queyranne, Maurice (2020), Faster Algorithms for Next Breakpoint and Max Value for Parametric Global Minimum Cuts, Integer Programming and Combinatorial Optimization, Springer International Publishing : Berlin Heidelberg, p. 27-39. 10.1007/978-3-030-45771-6_3

Type
Communication / Conférence
External document link
http://www.iasi.cnr.it/aussois/web/uploads/2020/slides/mccormickt.pdf
Date
2020
Conference title
21st International Conference, IPCO 2020
Conference date
2020-06
Conference city
Londres
Conference country
United Kingdom
Book title
Integer Programming and Combinatorial Optimization
Publisher
Springer International Publishing
Published in
Berlin Heidelberg
ISBN
978-3-030-45770-9
Number of pages
450
Pages
27-39
Publication identifier
Metadata
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Author(s)
Aissi, Hassene
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
McCormick, S. Thomas
Sauder School of Business [British Columbia] [Sauder]
Queyranne, Maurice
Sauder School of Business [British Columbia] [Sauder]
Abstract (EN)
The parametric global minimum cut problem concerns a graph G=(V,E) where the cost of each edge is an affine function of a parameter μ∈Rd for some fixed dimension d. We consider the problems of finding the next breakpoint in a given direction, and finding a parameter value with maximum minimum cut value. We develop strongly polynomial algorithms for these problems that are faster than a naive application of Megiddo’s parametric search technique. Our results indicate that the next breakpoint problem is easier than the max value problem.
Subjects / Keywords
Parametric optimization; Global minimum cut