PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Polynomially Searchable Exponential Neighbourhood for Graph Colouring
Adam Prügel-Bennett and Celia Glass
Journal of the Operational Research Society Volume 56, Number 3, pp. 324-330, 2005.

Abstract

In this paper we develop a new graph colouring strategy. Our heuristic is an example of a so called "polynomially searchable exponential neighbourhood" approach. The neighbourhood is that of permutations of the colours of vertices of a subgraph. Our approach provides a solution method for colouring problems with edge weights. Results for initial tests on unweighted K-colouring benchmark problems are presented. Our colour permutation move was found in practice to be too slow to justify its use on these problems. By contrast, our implementation of iterative descent, which incorporates a permutation kickback move, performed extremely well. Moreover, our approach may yet prove valuable for weighted K-colouring. In addition, our approach offers an improved measure of the distance between colourings of a graph.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:1763
Deposited By:Adam Prügel-Bennett
Deposited On:28 November 2005