The maximum cardinality cut problem in co-bipartite chain graphs
Arman Boyacı (),
Tınaz Ekim () and
Mordechai Shalom ()
Additional contact information
Arman Boyacı: Bogaziçi University
Tınaz Ekim: Bogaziçi University
Mordechai Shalom: Bogaziçi University
Journal of Combinatorial Optimization, 2018, vol. 35, issue 1, No 19, 250-265
Abstract:
Abstract A co-bipartite chain graph is a co-bipartite graph in which the neighborhoods of the vertices in each clique can be linearly ordered with respect to inclusion. It is known that the maximum cardinality cut problem ( $${\textsc {MaxCut}}$$ M A X C U T ) is $${\textsc {NP}}{\text {-hard}}$$ NP -hard in co-bipartite graphs (Bodlaender and Jansen, Nordic J Comput 7(2000):14–31, 2000). We consider $${\textsc {MaxCut}}$$ M A X C U T in co-bipartite chain graphs. We first consider the twin-free case and present an explicit solution. We then show that $${\textsc {MaxCut}}$$ M A X C U T is polynomial time solvable in this graph class.
Keywords: Maximum cut; Co-bipartite graphs; Dynamic programming; Chain graph; 68R10; 05C85 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10878-015-9963-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:jcomop:v:35:y:2018:i:1:d:10.1007_s10878-015-9963-x
Ordering information: This journal article can be ordered from
https://www.springer.com/journal/10878
DOI: 10.1007/s10878-015-9963-x
Access Statistics for this article
Journal of Combinatorial Optimization is currently edited by Thai, My T.
More articles in Journal of Combinatorial Optimization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().