An Ant Algorithm for the Partition Graph Coloring Problem View Full Text


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Chapter Info

DATE

2015-02-04

AUTHORS

Stefka Fidanova , Petrică C. Pop

ABSTRACT

In this paper we propose an Ant Colony Optimization (ACO) algorithm for the partition graph coloring problem (PGCP). Given an undirected graph \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G =(V,E)$$\end{document}, whose nodes are partition into a given number of the node sets. The goal of the PGCP is to find a subset \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$V^* \subset V$$\end{document} that contains exactly one node for each cluster and a coloring for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$V^*$$\end{document} so that in the graph induced by \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$V^*$$\end{document}, two adjacent nodes have different colors and the total number of used colors is minimal. The performance of our algorithm is evaluated on a common benchmark instances set and the computational results show that compared to a state-of-the-art algorithms, our ACO algorithm achieves solid results in very short run-times. More... »

PAGES

78-84

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-15585-2_9

DOI

http://dx.doi.org/10.1007/978-3-319-15585-2_9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1053332177


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