EconPapers    
Economics at your fingertips  
 

Tackling the maximum happy vertices problem in large networks

Dhananjay Thiruvady (), Rhyd Lewis () and Kerri Morgan ()
Additional contact information
Dhananjay Thiruvady: Deakin University
Rhyd Lewis: Cardiff University
Kerri Morgan: Deakin University

4OR, 2020, vol. 18, issue 4, No 6, 507-527

Abstract: Abstract In this paper we consider a variant of graph colouring known as the maximum happy vertices problem. This problem involves taking a graph in which a subset of the vertices have been preassigned to colours. The objective is to then colour the remaining vertices such that the number of happy vertices is maximised, where a vertex is considered happy only when it is assigned to the same colour as all of its neighbours. We design and test a tabu search approach, which is compared to two existing state of the art methods. We see that this new approach is particularly suited to larger problem instances and finds very good solutions in very short time frames. We also propose a algorithm to find upper bounds for the problem efficiently. Moreover, we propose an algorithm for imposing additional precoloured vertices and are hence able to significantly reduce the solution space. Finally, we present an analysis of this problem and use probabilistic arguments to characterise problem hardness.

Keywords: Tabu search; Graph Colouring; Maximum happy vertices problem; 68; 90 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10288-020-00431-4 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:aqjoor:v:18:y:2020:i:4:d:10.1007_s10288-020-00431-4

Ordering information: This journal article can be ordered from
https://www.springer ... ch/journal/10288/PSE

DOI: 10.1007/s10288-020-00431-4

Access Statistics for this article

4OR is currently edited by Yves Crama, Michel Grabisch and Silvano Martello

More articles in 4OR from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-20
Handle: RePEc:spr:aqjoor:v:18:y:2020:i:4:d:10.1007_s10288-020-00431-4